phd in statistics in australia

PhD in Statistics

The PhD program in Statistics at the Research School of Finance, Actuarial Studies and Statistics (RSFAS) equips graduates with knowledge of developments in theoretical and applied statistics. The PhD program draws upon the diverse expertise of academic staff across the University. The School’s PhD candidates will undertake independent research on a specialised research topic.

The program is focused on developing candidates for a career in academia, government or industry. Positions in government or industry may include researchers in scientific, medical or health research organisations; researchers or analysts within government agencies, such as the Australian Bureau of Statistics and Australian Institute of Health and Welfare, or departments of Health, Agriculture, Education, Finance and Treasury; researchers or quantitative data analysts within the corporate sector, including banking, finance and insurance, pharmaceutical, and energy and mining sectors; and management and statistical consultants.

CRICOS #: 048345A

Duration: 2 to 4 years full time (4 to 8 years part time)

Before you submit an application for entry to the program, you should:

• ensure you meet the admission requirements outlined below
• identify potential supervisors – that is, one or two statistics academics at ANU who conduct research in your area of interest.

You can find information on researchers and their research areas in the  ANU researchers database  and on the  RSFAS Statistics faculty  page.

While other ANU schools may recommend contacting potential supervisors before submitting an application,  this is not required  for entry into RSFAS’s PhD programs. Instead, you only need to list the name(s) of potential supervisors in your online application form.

Potential supervisors cannot guarantee entry into the PhD program. Admission will depend on the strength of your application relative to others in the pool.

After you’ve completed the steps above, you can proceed with an  online application .

Application deadlines

The first semester of the ANU academic year starts in February, and the second semester starts in July. While all applications for first semester entry must be submitted  before 31 October,  international applicants wishing to be considered for an  ANU scholarship  should submit their applications  before   31 August .

To be considered for a scholarship, your application must be accompanied by all the supporting documents listed below, including the referee reports. Request for referee reports are triggered and sent to your nominated referees at the time of submission of program application. It is thus important that you submit your application in advance (2-3 weeks) to allow time for your referees to provide their reports prior to the scholarship deadline.

If you’re currently completing an academic degree and haven’t yet received your final results and transcript, you should still submit all available documents before the deadline, and forward remaining results once you receive them. We won’t make a final decision on your application until we’ve received all the required documents.

The admission requirements for the PhD program in Statistics reflect the advanced knowledge that candidates will need to undertake the coursework component of the degree, and the research experience and skills needed to successfully undertake and complete the research thesis.

The minimum qualification requirement for admission to the PhD program in Statistics is:

• an Australian Bachelor degree (or equivalent) with First Class Honours or Second Class Honours Division A in statistics (or a related discipline), or
• another qualification (e.g. a Master degree) with a substantial research thesis component that the RSFAS HDR (higher degree by research) committee is satisfied is equivalent or superior to a degree mentioned in (a), or
• a combination of qualifications and professional experience that the RSFAS HDR committee is satisfied is equivalent or superior to a degree mentioned in (a).

Admission to the PhD program in Statistics is competitive and we can only admit a limited number of applicants each year. Meeting the minimum entry requirements does not guarantee you a place in the program.

If you don’t have sufficient research experience for entry into the PhD program, you might consider applying to the MPhil program . If you’d like to consider this pathway, contact the RSFAS HDR convenor for more information.

English language requirements

All applicants must satisfy the University’s  English language admission requirements . An international applicant who is not a native English speaker may satisfy these requirements by submitting evidence of an  IELTS  overall score of at least 6.5, and with no component less than 6.0, or a paper-based  TOEFL  score of at least 570, with at least 4.5 in the essay component.

Application and supporting documentation

You must submit your application online via the  ANU Application Manager .

In addition to the standard information required in the online application, you must submit the following supporting documents as part of your application:

• a one-page statement of purpose outlining your motivation to undertake a PhD in Statistics at ANU
• a research proposal – see details below, as well as these guidelines on how to  prepare a persuasive research proposal
• copies of written research work, e.g. honours or Master thesis, research project or published works
• official  TOEFL  or  IELTS  results (where applicable) to demonstrate that you satisfy the University’s  English language requirements .

Research proposal

The online application requires you to submit a research proposal. The proposal should set out an original research idea, provide an introduction or background to your research idea, clearly set out the objectives, data required and expected research methods, and explain why the research is important and the contribution it will make to the discipline. Among other things, the research proposal will require you to demonstrate an understanding of the key literature in your chosen topic area. As a guide, you should aim for between 1,500 and 2,000 words, including a list of key references.

The RSFAS HDR committee uses the research proposal as an indicator to assess the quality and originality of your ideas and your skills in critical thinking. Note that the research proposal does not restrict you to this field of study should you be admitted to the PhD program.

Offers of admission

The RSFAS HDR committee will review all complete applications submitted by the relevant deadline.

If your application is short-listed, you may be required to attend an interview (face to face or online).

We may send you an offer of admission if you satisfy the eligibility criteria and your area of interest matches those of RSFAS academics with supervisory capacity. However, since admission is competitive and supervisory capacity is limited, we won’t send any offers of admission  after the relevant application deadline , irrespective of the date when you submit your application.

The PhD program in Statistics consists of two components –  coursework  and  research .

Candidates undertake the research component after successfully completing the required coursework.

PhD coursework component

PhD candidates may be required to complete up to six semester-length courses during the first year of the program. Required coursework must be completed to a satisfactory level for candidates to progress to the research component. The specific coursework requirements will depend on each candidate’s background and will be determined through discussion with the HDR convenor and the chair of the candidate’s supervisory panel.

Compulsory courses for the PhD in Statistics are:

• STAT8027  Statistical Inference
• STAT8056  Advanced Mathematical Statistics
• STAT7040  Statistical Learning
• STAT7018  Stochastic Modelling

Candidates select up to two electives from graduate-level courses in statistics (or suitable advanced courses from other disciplines) in consultation with the chair of the supervisory panel.

PhD research component

Following the successful completion of coursework, PhD candidates undertake specialised research training and independent research.

Research supervisory panel

When a PhD candidate is admitted to the program, a provisional supervisor is appointed. The provisional supervisor has the responsibility of overseeing the candidate’s progress until a supervisory panel is chosen. During the first year, it is important that candidates start developing their research topic ideas by consulting with their provisional supervisor and other academic staff within RSFAS.

Either in a candidate’s first year of study, or soon after completion of their coursework, a supervisory panel will be chosen. The role of the panel is to assist, advise, and provide support and encouragement to the candidate for a timely and successful completion of the research thesis. The HDR convenor will determine the composition of the supervisory panel in consultation with the candidate.

RSFAS statistics seminar program

The RSFAS statistics seminar program consists of regular seminars presented by national and international researchers. PhD candidates are expected to attend and actively participate in the seminars throughout their candidature.

Research integrity training

Within three to six months of enrolment, all PhD candidates must complete the  Research Integrity Training  and pass the exam. Completion of this course and exam is a compulsory milestone for all PhD candidates.

Thesis proposal review

During the second year, candidates must submit a thesis proposal for review to their supervisory panel and present their proposal as a seminar to the School. The purpose of the thesis proposal review is to assess the originality, significance, adequacy and achievability of the candidate’s thesis plan.

The proposal includes a description of the research to be undertaken in the thesis, and a summary of the thesis structure and time plan.

Successful completion of the thesis proposal review (as determined by the Delegated Authority following consultation with the HDR convenor and supervisory panel) is required to continue in the PhD program.

Annual progress review

It is University policy that each candidate’s progress be reviewed periodically. In each year of their program, PhD candidates are required to submit an  annual plan and report  as a basis for periodic progress review. This document provides details on work completed by the candidate since the previous review, current progress, and any problems that may impact their research. It also outlines the coursework and research the candidate intends to undertake in the following 12 months.

Oral presentation

In their final year, candidates are required to give a final  oral presentation  on their research, usually three months before submitting their thesis.

Read more about  research candidate milestones .

Thesis submission and examination

The culmination of the PhD in Statistics is a written thesis which, upon completion, is submitted for examination. The thesis is examined by examiners who are experts in the relevant field.

For more information on the process, visit our page on  submitting a thesis .

For information about scholarships available to HDR candidates, visit our page on  scholarships and fees .

Read details of some of our alumni’s recent  job placements .

See our list of current  Statistics PhD students .

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• Research grants
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Submit your application along with your research proposal, CV, academic referee reports, academic transcripts and other supporting documents such as identification and evidence of residency status. Applications are made via the University’s online application portal.

Postgraduate program

The School of Mathematics and Statistics offers Higher Degree by Research (HDR) programs leading to the degrees of Doctor of Philosophy (Science) and Master of Philosophy (Science).

The School also offers the Master of Mathematical Sciences degree, and the units of study STAT5002 and STAT5003 form part of the Master of Information Technology .

NEW in 2024 In 2024 the Master of Data Analytics will be offered for the first time. This fully online course offers a breadth of data analytics knowledge, covering a multitude of qualitative and quantitative data research methods and their applications across industries, including business, health care, architecture, and political science.

For current and newly enrolled postgraduate students

Students should read the "School of Mathematics and Statistics higher degree by research procedures" document.

Please note that HDR candidatures and examinations of theses are managed by the HDR Administration Centre (HDRAC). To find detailed information on important matters such as:

• enrolment, research periods and census dates,
• compulsory HDR units of study: Work, Health and Safety (WHS), Responsible Research Practice, and Human Ethics,
• supervisory arrangements, in particular, requesting to change a supervisor,
• Faculty milestones: research plan, research seminar, first year report, intermediate research presentation, final research report,
• research progress: progress plan, first-year integrity check, annual progress review (APR),
• financial support for travel to attend conferences, workshops, and summer/winter schools through the Postgraduate Research Support Scheme (PRSS),
• travel insurance policy,
• requesting leave of absence or suspension from your research,
• recommencing of your studies after suspension,
• applying for an extension of candidature,
• preparation of your thesis and thesis composition,
• thesis submission procedure,
• examination process and outcomes,
• final thesis lodgement and graduation ceremony.

Degree entry requirements: Doctor of Philosophy (Science)

Applicants for a PhD (Science) program MUST hold a Master's degree or a Bachelor's degree with First Class Honours from the University of Sydney or an equivalent qualification from another university or institution. Further information about applications for admission, applications for scholarship, fees and deadlines for domestic and international students can be found on the Sydney Courses Doctor of Philosophy webpage.

Degree entry requirements: Master of Philosophy (Science)

Applicants for a MPhil (Science) program should hold a Bachelor's degree or an equivalent qualification. Further information about applications for admission, applications for scholarship, fees and deadlines for domestic and international students can be found on the Sydney Courses Master of Philosophy webpage.

Degree entry requirements: Graduate Diploma in Science

The Graduate Diploma in Science provides an alternate entry qualification for PhD. It is identical in content to the Honours (4th year) course and is available to candidates who are not eligible to enrol in that course, usually because of their background in Mathematics or Statistics from outside the University of Sydney. Graduate Diploma is a full fee-paying course. Further information about applications and fees can be found on the Sydney Courses Graduate Diploma in Science webpage.

Scholarships

• domestic students have to submit two separate applications: the PhD/MPhil application and the scholarship application,
• international students only click the relevant box in their PhD/MPhil application.

Study abroad and student exchange

Study abroad and student exchange are the two main program options for students enrolled at international universities and looking to study at the University of Sydney as part of their degree.

• As an exchange student you remain enrolled full time at your home institution while you attend the University of Sydney. While you are in Sydney you will continue to pay your usual tuition fees and other student fees to your home institution. A student from the University of Sydney will do the same in reverse, and the result is an exchange of students and places.
• Study abroad is a separate program from student exchange and involves a student enrolling and paying fees directly to the University of Sydney. There is no reciprocal exchange agreement.

Enquiries about postgraduate study in the School should be directed to the School's Coordinator of Postgraduate Studies Associate Professor Zsuzsanna Dancso by email [email protected] .

Mathematics and Statistics at Sydney

The School of Mathematics and Statistics offers a postgraduate program that is varied and flexible, catering for students of many different backgrounds. The School supports a policy of active research and insists on the highest standards of academic achievement. At present, the School consists of four research groups: Applied Mathematics, Mathematical Statistics, Nonlinear Analysis and Pure Mathematics. The Pure Mathematics group is further divided into three subgroups: algebra, computational algebra, and analysis, geometry & topology.

The School holds regular seminars, workshops and conferences that ensure that its members stay abreast of latest developments. It also supports an active program of long term and short term visits by distinguished international academics.

The School has all the facilities of a well established and progressive teaching and research institution, including a modern library and an extensive computer network of workstations. In addition the network supports a number of high-speed processors and colour graphics systems. A wide variety of software packages is available including Magma (developed in the School), Spida, S-plus, Reduce, Mathematica and Matlab.

The School is proud of its postgraduate students. Our research students are a valuable resource and the School is committed to providing them with excellent research facilities and office space in which to work. Some financial aid is available to students to allow them to attend relevant conferences and workshops. Further support is offered in the form of part-time teaching, assignment and examination marking.

Sydney and the University

Sydney is the oldest and largest city in Australia, and the capital of New South Wales. The city has a population of over four million and operates as an international centre for commerce, finance and the arts for the Asia-Pacific region. Sydney is well known for its great natural scenic beauty, beaches and climate, as well as its high quality of life.

The University of Sydney, established in 1850, is the oldest of all the universities in Australia. It has nine colleges of residence for students and visiting scholars. It has two theatres, an art gallery, several museums and a thriving cultural life in all facets of the arts. For the physically active there is a wide range of sports facilities, including a covered full-size olympic pool, tennis and squash courts, two sporting ovals, gymnasiums, sports instructors and physiotherapists. Every effort is also made to accommodate the physically impaired.

The diversity of courses and degrees the University offers is unequalled in the country. It provides a lively and challenging environment in which to pursue all aspects of academic life.

The Australian academic year begins in late February. It is divided into two semesters with a winter break of about three weeks from mid-June through to mid-July. Coursework programs finish at the end of November.

Maths & Stats website:

• Undergraduate Program
• Prospective Students

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Doctor of Philosophy

A Doctor of Philosophy (PhD) is an internationally recognised graduate research program that will enable you to become an independent researcher. 

With the guidance of an advisory team, you'll undertake a research project, produce an 80,000-word thesis and complete an oral examination.

A PhD takes 3 to 4 years full-time. Under guidance, you'll develop advanced research skills and knowledge in your chosen field.

The thesis is a substantial document that makes an original contribution to your field of research. Your thesis may involve an alternate format .

You'll need a strong academic background and you may need to submit a research proposal and other documents to support your application. About 1,000 PhD candidates join UQ each year researching a wide range of topics.

Research at UQ

UQ is one of Australia’s top research-intensive universities. Our research makes an impact on the world's cultural, environmental, economic and social challenges.

Learn more about UQ's research

Program highlights

• Be inspired and challenged to explore new ideas and develop greater understanding of complex questions with leading researchers.
• Access premier resources including one of Australia’s largest libraries, with more than 2 million physical resources and 116,800+ journal subscriptions.
• Foster and improve your skills through the Career Development Framework, created with industry.
• Learn from researchers whose work addresses national and global cultural, environmental, economic and social challenges.

35 in the world

CWTS Leiden Ranking 2023

51 in the world

Academic Ranking of World Universities 2023

Supervision

You have to find and contact a thesis supervisor before you apply

This supervisor will support, guide and mentor you through your research, and can introduce you to professional networks that will start your career.

Find a supervisor

3-Minute Thesis

The showcase event for research candidates is the 3-Minute Thesis (3MT). 

3MT is held each spring.

Learn more about the 3MT

Career development

UQ offers a range of development opportunities via the Career Development Framework (CDF) to help you develop portable skills for any career or industry.

Learn more about the CDF

Studying at UQ gave me the flexibility to expand my knowledge across different areas of science outside of my chosen specialty. Keeping my scientific and translational skills broad has allowed me to adapt to different environments and opportunities throughout my career.

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Entry requirements, gpa equivalent.

Select where you studied and your qualification to see the GPA you need to be considered for this program.

Meeting the GPA requirement doesn’t guarantee admission.

Academic entry requirements

You have to prove you are prepared for PhD study. You do this by showing you:

• have completed some research experience
• have completed an approved university degree  and
• can meet the English language requirements.

Approved degrees

An approved degree needs to be:

• in an area relevant to your proposed PhD project and
• completed no more than 10 years ago.

You need one of the following approved degrees to apply for a PhD:

• Master of Philosophy (or another research master’s degree); or
• Bachelor’s degree from an approved university with at least honours class IIA or equivalent; or
• Coursework master’s degree with an overall grade point average of 5.65 on the 7-point UQ scale which includes relevant research experience, approved by the dean; or
• Postgraduate degree (at least one year full-time or equivalent) with an overall grade point average of 5 on the 7-point UQ scale, together with demonstrated research experience equivalent to honours class IIA will be considered on a case-by-case basis; or
• Bachelor’s degree plus at least 2 years of relevant research experience , including research publications.

Research experience

You'll meet the requirements for admission into a PhD in terms of 'research preparedness' if you can provide evidence that you've planned and executed project work and/or a body of research with some independence.

To demonstrate this, we'll ask you to provide one of the following:

• with completed courses that aim to develop research skills (minimum value of #1 unit e.g. 50 per cent of a #2 unit course), and/or
• the completion of a supervised research project that includes an individually graded written report with a combined minimum course volume equal to #4 units at UQ.
• Scholarly papers involving a substantial contribution as an author, appearing in recognised academic journals or in volumes published by recognised academic publishers.
• Research or technical reports prepared for industry, government or business, which adhere to the broad conventions of academic publishing (i.e. contain an up-to-date review of relevant literature, a description of relevant research methods and an evaluation of results, etc.) and which identify you as a significant contributor.
• A portfolio of published creative work together with published critical discussion of some or all of that work, or of a comparable body of work by others, and which demonstrates your development of a scholarly approach to creative work as research investigation.
• Demonstrable industry or work experience where you can demonstrate that you have planned and executed a project, working with a high level of independence.

Student visas

International students who are accepted into full-time study in the Doctor of Philosophy are eligible to apply for an Australian Student visa (subclass 500).

This program has two CRICOS codes:

• 0100213 – Architecture, creative arts, education, health, information technology, management and commerce, mathematical sciences, social and cultural studies
• 0100214 – Agriculture and environmental studies, dentistry, engineering, human movement, medical studies, natural and physical sciences, pharmacy, psychology, veterinary science

Discuss your proposed project with us to determine which CRICOS code is most relevant for your visa application.

There are a number of requirements you must satisfy before a visa is granted, including the genuine temporary entrant (GTE) requirement.

Learn more about student visas

Additional entry requirements

Many departments will have additional entry requirements and may request documents to support your application, such as a research proposal. You should discuss these additional requirements with your potential thesis supervisor.

Additional application information

Minimum English language proficiency requirements apply, please refer to the English proficiency policy .

English language requirements

There are a few ways you can meet our English language requirements. If you sit a test, the following scores are needed for PhD admission:

Read our English language requirements

Scholarships

There are several types of PhD scholarship:

• tuition fee scholarship : this covers the fees charged by UQ for PhD study
• living stipend scholarship: this is a   fortnightly payment (or stipend) to support your daily expenses
• top-up scholarship: may be provided by external organisations, supervisors, or philanthropic donations. When awarded, they provide an additional payment on top of a living stipend scholarship. They cannot be held without a living stipend scholarship.

Each year, we award more than 600 scholarships to attract and support the highest quality higher degree by research applicants.

View all postgraduate research scholarships

University scholarships

UQ scholarships include:

• Graduate School Scholarships
• Graduate School Tuition Fees Scholarship
• Aboriginal and Torres Strait Islander Scholarships
• Earmarked Scholarships
• The Graduate School Scholarship

Other scholarships

Throughout the year we advertise a range of other research scholarships, including top-up scholarships, travel grants and external scholarships, including:

• Westpac Future Leaders Scholarship

How to apply for a scholarship

You can apply for many scholarships using the same form as your PhD application. External scholarships might have different ways to apply. 

Our Scholarships website explains how to apply for each scholarship. If you are applying for a non-UQ scholarship, outcome dates may vary.

Fees and costs

Tuition fees.

Your fees will vary according to your academic field, study load and whether you study internally or remotely.

Learn more about postgraduate research fees

Research costs

The department you enrol with will meet all necessary costs for your project, including:

• resource and facility costs: at UQ, which may include other organisations in Australia or overseas
• travel costs: to complete fieldwork, collect data, or to visit libraries or other repositories
• coursework costs: for courses studied outside the department
• relevant training: in particular methodologies or techniques.

How to apply

Before you apply, 1. check your eligibility.

Check your eligibility by reviewing the entry requirements for UQ's Higher Degrees by Research. If applying for a scholarship, check the scholarship's eligibility and important dates.

2. Approach a potential supervisor or find a project

You'll either need to find:

• a supervisor in your field who will support your proposed project.  Identify a researcher .
• a project you can join that suits your interests.  See available projects .

If you're choosing a researcher, you'll need to find one with relevant expertise and get agreement to support your PhD and project.

Many departments will require additional information to make a decision around your motivation, understanding, commitment, and financial support required.

They may request documents to support your application, such as a research proposal. You should discuss these additional requirements with your potential thesis supervisor.

3. Gather your documents

You will need to compile the necessary documents. We will accept scanned copies of original documents, but you will have to keep all original documents for the duration of your studies.

Upload all documents as PDFs and name your files like this: LASTNAME_firstname_document-name.pdf

If any of your documents is in a language other than English, you will need to send both the original document and an official translation.

Send the following documents with your application:

An academic CV assists us to determine your readiness to commence a higher degree by research. For the purposes of this application, your academic CV should be current (i.e. no more than 6 months old) and include information under the following headings:

Personal details

• your full name
• your contact details (phone number, email address, city and country of residence)
• nationality
• languages spoken and proficiency level for each
• your ORCID ID or other research output identifier (such as Google Scholar) if you have one (see the ORCID ID and research identifiers information provided by UQ Library).

As the purpose of this academic CV is to determine your academic suitability for a higher degree by research program at UQ and your competitiveness against other applicants, we only require information that is of direct relevance to our decision-making processes. With this in mind, please do not include the following in your academic CV:

• photographs/head shot
• marital status
• driver’s license
• date of birth/age
• hobbies and interests.

Educational qualifications and academic awards

List each of your formal educational qualifications in reverse chronological order (i.e. with the most recent formal educational qualification listed first). For each qualification, include:

• the commencing and end dates (month and year) for the qualification
• the full title of the qualification (e.g. Bachelor of Arts instead of B.A.)
• the institution attended and the enrolling school/administrative unit
• the city and country where the institution is located
• your Grade Point Average (GPA) for the overall qualification
• any academic achievement awards (e.g. Dean’s awards, subject prizes, University medals, thesis prizes etc.) received for the qualification
• if a research thesis was part of the qualification, include the title and word length of your dissertation.

As part of your application, please submit academic transcripts and degree certificates for each educational qualification you list.

Please do not include:

• high school qualifications
• the individual subjects/courses undertaken throughout your qualifications or the grades awarded for these
• training courses/professional development activities not resulting in a formal qualification.

Professional affiliations and memberships

List any professional/disciplinary associations or committees that you a member of and include:

• the commencing and end date (in years) for the affiliation/membership
• the name of the professional association or committee
• your membership type (e.g. student member, affiliate member, full member etc.) or role (e.g. committee member, secretary, president etc.).

Employment history

List each of your previous employment roles in reverse chronological order (i.e. with the most recent/current employment listed first) and include:

• the commencing and end dates (month and year) for the employment
• the title of each position
• the name of the employing organisation, the city, and country where you were based
• your main duties or accountabilities in that role, providing detailed information on any research-related activities
• any achievements during that role that are relevant to your proposed field of research .

Other research experience

List any voluntary, unpaid, or extra-curricular research-related projects or experiences you have undertaken (e.g. summer research projects, internships etc.) and include:

• the commencing and end dates (month and year) of the experience
• the name of the organisation, the city, and country where you were based

Research outputs

In reverse chronological order (i.e. the most recent output first) list your research outputs,  including for example research published or accepted for publication, research reports, and research by creative practice.

If needed, use sub-headings to separate refereed journal articles, published conference proceedings, edited book chapters, books, creative works, industry reports, invited papers, patents, media commentary, conference presentations and posters, invited talks etc. If applicable, use additional sub-headings to indicate if outputs are published , accepted for publication (but not yet in print), or (submitted but) under review .

Do not include any outputs/publications that are ‘in preparation’ .

For all research outputs, include:

• the output/publication reference using an official bibliographical style (such as Turabian/Chicago, APA, Harvard), including listing all authors in the order that they appear in the work with your name in bold
• the Digital Object Identifier (DOI), PubMed Identifier (PMID), International Standard Book Number (ISBN) or URL where applicable
• the standing of the journal or conference and the impact of the work (e.g. impact factors, citations and other metrics indicators)
• relevant indicators of national or international significance
• rejection rates for the outlet etc.
• how much of the original research you were responsible for (i.e. what was your role in the conception and design of the project and how involved were you in the analysis and interpretation of the research data on which the publication is based?)
• the extent to which you authored the paper.

Research grants and relevant awards

Include only those research grants and relevant awards that you have received at the time of making your application (i.e. do not list grants or awards that you applied for and did not receive or are awaiting a decision on). For each research grant/award, include:

• the name of the granting/awarding body and the country in which they are based
• the name of the grant/award
• the year(s) in which the grant was active or the year in which the award was made
• the amount of the research grant/award
• if relevant (e.g. for research grants), the title of your application.

Applicants from creative and professional-based disciplines may also include non-research grants and awards related to their creative or professional practice.

Research achievements relative to opportunity (optional)

In recognition of the diverse personal and professional pathways that applicants have experienced, you are invited to provide information ( maximum 200 words ) to contextualise your research outputs and achievements, relative to the opportunities that you have had to participate in research-related activities.

This section of the CV is optional and should only be included if you believe there are factors relevant to your research achievements that you would like the selection panels to know. Examples of factors include (but are not limited to):

• study/career disruptions due to illness, caregiving, natural disasters etc.
• non-linear academic or career progression, or a change in career direction
• reduced ability to take up research-related opportunities (e.g. attend conferences) due to caregiving responsibilities.

Academic referees

Please provide us with two referees who can comment on your academic work. For each referee, include their:

• honorific and name
• employing organisation and the city and country where they are located
• contact details, including office address, telephone, fax and email (preferably an institutional, rather than private, email address)
• an indication of the capacity in which you know this person (e.g. were they a lecturer or thesis supervisor, an employer, how long you’ve known them etc.). 

If possible, please include at least one:

• senior person (preferably your supervisor or the head of your organisational unit) closely associated with your current work, and
• person who is not a member of your proposed advisory panel/supervisory team.

Formatting and document specifications

We recommend that you use the below formatting settings to improve the readability of your CV:

• margins of at least 1.5 centimetres
• single line spacing
• no smaller than 12 point Times New Roman font (or equivalent)
• left justify text (not full justify)
• include your name and page number on each page
• be consistent in your formatting and spelling throughout
• limit the use of bold, underline, italics, and multiple font types.

Please proofread your CV carefully before uploading it to your application.

Save as a PDF and name your file: LASTNAME_firstname_CV.pdf

There is no page limit to your academic CV – it can be as long as required to include the information requested here.

Please include in your CV all the headings listed above – if you do not have any content to add for a particular heading please list ‘None to date’ under that heading .

An academic CV for employment purposes within Australia would not include the information requested here outlining your three most significant publications or your research achievements relative to opportunity. It would, however, include information about professional and service activities undertaken and may include a summary of your relevant research/teaching interest areas and skill sets – this information is not required in the CV you submit here for application to an HDR program.

This should show all study you have undertaken since secondary school, whether complete or incomplete, including the institution grading scale. The grading scale is often found on the final page or the reverse page; be sure to include all pages.

An academic transcript can also be called an:

• academic record
• diploma supplement
• statement of learning
• record of achievement.

A degree certificate is a legal document, imprinted with a university seal. It should state the name of your qualification and areas of study.

Include all degree certificates (testamurs) for post-secondary study with your application. If you studied in China, you must provide a:

• award certificate and
• graduate statement/certificate.

All applicants have to prove they can meet English language requirements . Any test scores have to be valid at your proposed commencement date.

Include a copy of the information page (with your photo) in your passport. This will verify your identity and ensure we can make offers correctly.

Include the contact details of two referees who will support your application. These referees will need to provide insight into your research experience.

We will contact your referees for a report, but you will need to enter their details into the application form.

Other documentation, originals or certified copies, may be required depending on your individual circumstances, for example:

• evidence of change of name
• proof of citizenship, if you are not a citizen of Australia or New Zealand by birth
• evidence of your Aboriginal and/or Torres Strait Islander status
• previous research program information .

If you don't provide us with all documents it will take us longer to process your application. Your start date might then be delayed, or you might miss an admission or scholarship deadline. 

4. Apply online

Once you have prepared your application and contacted a potential supervisor, use the online application form to apply. Your application can only be assessed once your referees have responded to us, and all outstanding documents and school/institute endorsements have been received.

Important dates

The academic year for research students is divided into four research quarters (RQ).

Candidates applying for a Student Visa or UQ scholarship may need to apply earlier. Make sure you check  scholarship round application deadlines  and outcome dates before applying.

The agreed start date will be included on your Confirmation of Enrolment.

Find out more about research quarter dates

The academic year for research students is divided into four research quarters (RQ). You can start a PhD in any quarter, as long as the Census Date hasn't passed.

Candidates applying for a UQ scholarship may need to apply earlier. Make sure you check scholarship round application deadlines and outcome dates before applying.

The agreed start date will be included on your offer of admission.

Aboriginal and Torres Strait Islander applicants

For support with applying – or if you have any questions about university life – get in touch with our Aboriginal and Torres Strait Islander Studies Unit.

Contact the ATSIS Unit

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School of Mathematics and Statistics

Employment opportunities

Latest news and events

The University of Melbourne's School of Mathematics and Statistics is one of Australia's leading mathematics and statistics schools. The School offers a wide range of subjects to undergraduate and postgraduate students.

• PhD scholarship opportunities
• Study with us

Completing studies in mathematics and statistics will give you powerful tools to understand the world. Consider studies in an undergraduate degree, or at a graduate level to conduct research.

Current students

Current students can find resources, links and important information.

Research prospectus

Faculty of Science researchers conduct diverse and varied research in our state-of-the-art facilities. Our scientists are global leaders in their fields, finding solutions to the biggest issues we face today.

The research within the School of Mathematics and Statistics covers areas of pure and applied mathematics and statistics. A broad school with an international reputation, we have research foci in Algebra, Continuum Modelling, Discrete Mathematics, Geometry and Topology, Operations Research, Mathematical Biology, Mathematical Physics, Stochastic Processes, Statistics, and Data Science.

Explore our research prospectus to find out what projects our leading academics are investigating.

Download the prospectus  (PDF 8.1 MB)

Learn more about our research

Research groups.

The School of Mathematics and Statistics has a very active research component. Read more about the research conducted here, and the researchers involved.

Research Centres

The School of Mathematics and Statistics is associated with several research centres.

Upcoming seminars based on research by staff at the School of Mathematics and Statistics.

Connect with us

If you would like to study with us, or discuss opportunities for collaboration or helping to fund our work, see below for how to get in touch.

Join over 10,000 students at the Faculty of Science with a range of honours, graduate, and research degrees. Visit  Study with us – graduate research for information and enquiries about graduate studies.

Collaborate with us

The Faculty of Science invites interested organisations who would like to explore collaborative research or use our developed technologies. Please get in touch with our Business Development team to discuss.

Darren Coomber Business Development Director, Faculty of Science Innovation & Enterprise | Research, Innovation & Commercialisation Phone: +61 (3) 9035 5024 Email: [email protected]

Our generous benefactors make our work possible. Visit Support Mathematics and Statistics to find out how you can support our leading research and help change the lives of future generations by funding science scholarships.

• Academic Staff

Teaching and research staff in the School of Mathematics and Statistics

• Professional Staff

Administrative, technical and support staff in the School of Mathematics and Statistics.

• Honorary Staff

Honorary appointees in the School of Mathematics and Statistics.

• Postgraduate students

Students undertaking PhD, MPhil and MSc qualifications in the School of Mathematics and Statistics.

• Upcoming events

Seminar series

View upcoming seminars and subscribe to seminar notifications.

• Algebraic Geometry and K-Theory
• Analysis and PDE
• Discrete Structures and Algorithms
• Learning and Teaching
• Mathematical Biology
• Mathematical Physics
• Melbourne Centre for Data Science
• Moduli Spaces
• Number Theory
• Operations Research
• Pure Mathematics
• Random Matrix Theory
• Representation Theory
• Stochastic Processes

Our initiatives

School outreach.

We work with primary and secondary schools to run a range of popular mathematics and statistics programs, including incursions, competitions and professional development opportunities for teachers.

Women in Maths and Stats

Every year Women in Mathematics Day is celebrated on the 12th of May. Get to know some of the women in the School of Mathematics and Statistics and learn about their journeys.

• Student Awards

These awards are granted to high-achieving students, in recognition of their academic success and overall performance in specific areas of their course. Students are nominated for these awards by the University teaching staff.

The School hosts many seminars, with speakers ranging from PhD students on the cusp of completing their studies to world-renowned experts in their fields.

Statistical and consulting services

The Statistical Consulting Centre (SCC) provides statistical and consulting services to business, industry, government and the academic world, bringing a wealth of knowledge to real-world issues in a practical, robust manner, as well as courses in statistical methods. The SCC's courses are open to anyone, and participants come from academia, business, industry and government.

Consulting services Statistical courses

International engagement

Melbourne-peking virtual research hub for mathematics and statistics.

This research hub promotes collaboration between The University of Melbourne and Peking University in the fields of teaching and research in mathematics and statistics.

Find out more

Connecting with alumni and students

We are passionate about sustaining a sense of community amongst our students and alumni, served by our student societies and alumni network.

Student societies Alumni information

Support Mathematics and Statistics

Our generous benefactors make it possible for us to recognise the achievements of our talented students, support development of early career researchers and make surprising fundamental research discoveries. This builds the foundation for our future stars, continuing excellence in the mathematical sciences to benefit its broader application in just about every aspect of life. We invite you to be one of our valued philanthropists to support our people and work.

Support our work

The University of Melbourne's School of Mathematics and Statistics is a world-leading school of mathematics and statistics. The School has achieved this status through the high quality of its research and teaching programs. We offer a wide range of subjects to undergraduate and postgraduate students and are involved in all aspects of community life that impacts on the discipline and its applications.

• Message from Head of School

We are a broad School with an international reputation covering areas of pure and applied mathematics and statistics, read more on what School of Mathematics & Statistics has to offer.

Leadership Team

View our academics who help to lead and coordinate School activities and committees.

Equity and diversity

The School of Mathematics and Statistics is strongly committed to providing support and resources to create an equitable environment for all members of the community, including students at all levels and visitors.

Get in touch with us if you have any general enquires or seeking information and guidance for academics.

• John Sader elected Fellow of the Australian Academy of Science
• Jobs at the School of Mathematics and Statistics
• 3 tips for Science undergraduates joining the workforce
• Melbourne technology boosts effort to map every cell in human body
• Exceptional Talent Scholarship
• Professor David Balding featured in The Age
• Heroines of mathematics
• Matilda to the Rescue
• Weighing Up Evidence in Criminal Courts and at a King's Burial Site
• Professor Anthony Guttmann honoured with Order of Australia
• COVID-19 modelling released from Doherty Institute
• ARC Future Fellowships announced for Maths & Stats
• Open Day at Maths and Stats
• Watch the Course Information Session
• Women in Geometry, Analysis and Topology
• New mathematics leads to innovative solutions
• Forecasting landslides from space
• Mathematician and role model elected Fellow of the Australian Academy of Science
• Using mathematical modelling to fight malaria
• Professor Michael Stumpf awarded prestigious ARC Australian Laureate Fellowship
• OPTIMA ARC Training Centre aims to transform industry through optimisation
• Academics join 2022 Superstars of STEM cohort
• Applications open for undergraduate and postgraduate awards
• Software developed by School of Mathematics and Statistics researcher shortlisted in prestigious Eureka Prizes
• New video series spotlights mathematical biology
• Science academics rank as world-leaders for research citations
• University confers Honorary Doctorate on mathematician
• Translating big data into better health thanks to major grant
• Problem-solving on a global stage: Students excel in international maths competition
• Avoidance, confusion, solitude: whales react to rising noise pollution
• Mathematicians moved by dance, karate and building a better world
• Supervision
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• List of Possible Supervisors
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• Mathematical Ecology, Epidemiology and Biosecurity
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Apply for Doctor of Philosophy - Mathematics and Statistics

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Mathematics and Statistics

Doctorate by research.

This offering version is phasing out and no longer taking applications. You may be able to apply for a later version.

• Qualification Doctor of Philosophy - Mathematics and Statistics

The Commonwealth Register of Institutions and Courses for Overseas Students (CRICOS) Code indicates a registered program offered to international students studying in Australia on student visas.

As a doctoral research degree candidate, you will uncover new knowledge either by the discovery of new facts, the formulation of theories or the innovative reinterpretation of known data and established ideas. Your research will use an in-depth understanding of theories and concepts to develop practical solutions for real-world problems.

A higher degree by research differs from other postgraduate degrees in that at least two-thirds of the study program must involve research. Although some coursework units may be required, the main part of your work will be in the form of a thesis written under the guidance of a supervisor and associate supervisor(s). Your thesis must, in the opinion of the examiners, be a substantial original contribution to the knowledge or understanding of any field through the discovery of new facts, the formulation of theories or the innovative reinterpretation of known data and established ideas. It must also demonstrate your capacity to conceive, design and complete independent research.

Throughout your studies, our faculties will provide you with access to equipment and resources to support your research, and financial assistance to attend appropriate local and international conferences.

Please refer to the handbook for additional course overview information. 

Why research at Curtin

Curtin is widely recognised for applied research firmly focused on solving real-world problems. Underpinning our research endeavours are strong partnerships with industry, business and government, which result in outcomes that greatly benefit the broader community locally, nationally and globally. Our international reputation for being a strong partner in industry-driven research ensures our graduates enjoy outstanding opportunities to become innovators in their fields.

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Professional recognition

Depending on your area of speciality, you may be eligible for membership of various professional organisations upon graduation.

Admission criteria

What you need in order to get into this course. There are different pathway options depending on your level of work and education experience.

Entry requirements for Australian and New Zealand students

Applicants are required to demonstrate a capacity to carry out independent research and have adequate training and ability to pursue the proposed research course. Generally, this may be a master degree or bachelor degree with first or upper second class honours. See the Section 3.2.1 of the  HDR admission policy  for detailed information.

English requirements

Curtin requires all applicants to demonstrate proficiency in English. Specific English requirements for this course are outlined in the IELTS table below.

You may demonstrate English proficiency using the following tests and qualifications .

IELTS Academic (International English Language Testing System)

Overall band score

Use your experience to get credit towards your degree

Finish your course sooner with credit for your previous study or work experience.

Fees and charges

Fee information is not available for this course at this time. Find estimated course fees .

Looking for more detail on the course structure?

The offering information on this website applies only to future students. Current students should refer to faculty handbooks for current or past course information.

The information on this page may be subject to change. In particular, Curtin University may change the content, method or location of delivery or tuition fees of courses.

While Curtin uses reasonable efforts to ensure that the information provided on this page is accurate and up to date, errors and omissions sometimes occur. Curtin makes no warranty, representation or undertaking (expressed or implied) nor does it assume any legal liability (direct or indirect) for the accuracy, completeness or usefulness of any information.

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• Curtin course code:  DR-MATHST
• CRICOS code:  043955D
• Last updated on:  21 May 2024

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Bachelor of Business Administration (BBA) Specialisations

Business specialisations available in the BBA:

• Accounting for Business Decisions Specialisation
• Business Law and Policy Specialisation
• Business Project Management Specialisation
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• User Experience for Business Optimisation Specialisation
• Workforce Management Specialisation

Specialisations available from Humanities and Science:

• Actuarial Financial Mathematics Specialisation
• Advertising Design Specialisation
• Animation and Game Design Specialisation
• Anthropology and Sociology Specialisation
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• Chinese Language Specialisation
• Construction Management Specialisation
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• History Specialisation
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• Interior Architecture – Applied Interior Design Specialisation
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• Social Inclusion and Equity Specialisation
• Social Justice Specialisation
• Surveying and Spatial Sciences Specialisation
• Theatre Arts Specialisation
• Urban Design and Planning Specialisation
• Web Media Specialisation
• Web Presence Specialisation

Bachelor of Commerce Specialisations

Business specialisations:

• Applied Finance Specialisation
• Banking Specialisation
• Employment Relations Specialisation
• Innovation and Entrepreneurship Specialisation
• Corporate Screen Production Specialisation

Bachelor of Innovation Specialisations

Specialisations available from Humanities, Science and the Centre for Aboriginal Studies:

• Biological Diversity Minor
• Climate Change Science Minor
• Environmental Management Minor
• Food Science Minor
• Forensic Studies Minor
• Geophysics Minor
• Geospatial Technology Minor
• Go Global – Internship Specialisation 1
• Go Practice – Internship Specialisation 1
• Indigenous Australian Cultural Studies Specialisation
• Landscape Restoration Minor
• Mapping and Land Planning Minor
• Metallurgy Minor
• Mining Minor
• Optimisation Minor
• Strategic Studies Specialisation

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Postgraduate research

Discover information for all postgraduate researchers including resources, guides and key requirements.

Postgraduate research students play an important and valued role in our school. Find out more about our postgraduate student community below.

Information for new students

Current research students

Postgraduate events

Postgraduate student awards and accolades

Information about research theses

Each August, the school showcases its achievements in research through the postgraduate conference. All postgraduate students are invited to present their research and practice research communication skills.

POSTGRADUATE RESEARCH CONFERENCE

Past research students

Michael Tallis PhD Research Travel Award

PhD projects

Entry requirements

Obtaining funding

Application & Fees

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Statistics and Data Science

Focus Bayesian computing Scalable methodology Data science Health statistics Population statistics Statistical modelling Group leaders Prof. James Brown Prof. Matt Wand

The UTS Statistics and Data Science group has interests that range from the development of fundamental statistical methods to the application of statistics in such areas as population health, forensics, and law. Much of this work is funded through grants from the Australian Research Council, as well as as well as through Australia's National Health and Medical Research Council (NHMRC) project grants, the Bill and Melinda Gates Foundation, and cooperation with Australian government bodies such as the Australian Bureau of Statistics. A major part of our work involves the development of new methodology to investigate complex problems in the age of Big Data. Specific sub-areas of statistical research include:

• Methodology for Big Data - development of scalable statistical methodology for analysis of high volume/velocity data involving machine learning paradigms; 
• Health related statistics - applications of statistical modelling within population health, sports science, and clinical trials;
• Statistical data science  - applications of machine learning to generate quantitative information for legal scholars, data wrangling and analysis of medical data; 
• Official statistics - use of government surveys combined with census and alternative data sources to produce key population statistics;
• Modelling and simulation of stochastic processes - development of methodology for the modelling and simulation of natural phenomena including applications in biology.

UTS acknowledges the Gadigal people of the Eora Nation, the Boorooberongal people of the Dharug Nation, the Bidiagal people and the Gamaygal people, upon whose ancestral lands our university stands. We would also like to pay respect to the Elders both past and present, acknowledging them as the traditional custodians of knowledge for these lands.

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PhD scholarship in Statistics and Data Analytics

A student with a strong background in statistics with Honours or Masters, excellent computing skills in R or Python, and an interest in working with biochemists and medical researchers. A student

Senior/Lecturers in Data Science / Stochastic Modelling / Statistics @Adelaide

for continuing Lecturer/Senior Lecturer roles in Stochastics, Statistics and Data Science. To be successful at Level B we are seeking: PhD in the mathematical sciences or equivalent qualification Demonstrated

Research Fellow - Biometry - Data scientists, statisticians (Agriculture)

the classification level. We are looking for someone with the following key capabilities: A PhD in a relevant discipline such as Applied Statistics , Mathematics, Bioinformatics, and/or Computational Genetics, Data

Lecturer in Statistical Data Science

criteria A PhD in machine learning, statistical data science, statistics or a related discipline. Demonstrated ability to conduct outstanding research in statistical data science as evidenced by independent

Associate Professor / Professor in Statistics or Statistical Data Science

at Associate Professor (Level D) A PhD in statistics , statistical data science or a related discipline. Demonstrated and sustained contributions to undertake outstanding research in statistics or statistical

Leveraging big data and AI/ML for smart transport solutions ( PhD scholarship)

Application dates Applications close15 July 2024 What you'll receive You'll receive: a stipend scholarship of $32,192 per annum for a maximum duration of 3.5 years while undertaking a QUT PhD . The

Lecturer/Senior Lecturer in Data Science/Applied Statistics

have a PhD and demonstrated expertise in applied statistics , data science or equivalent.  The successful applicant will also have a strong commitment to quality teaching and learning, experience working

Associate Professor/Professor

computational expertise in mathematics, statistics and computing with applications in materials science, power engineering, quantum physics, signal processing, astronomy, industrial optimisation and data science

Lecturer in Data Science @USyd

PhD or a doctorate in Mathematics, Applied Mathematics, Statistics , or related field an outstanding track record of publishing their research in areas of data science, optimization, or applied

Associate Research Fellow / Research Fellow, Biostatistics

disseminate findings through conference papers and publications. To be successful, you’ll have: Associate Research Fellow: Master’s degree in Biostatistics or Statistics ; alternatively, a PhD in Epidemiology

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Applied statistics research

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Members of the Applied statistics research area develop, apply and evaluate statistical solutions in a broad number of areas including sport, medicine, IT, water, food and manufacturing industries.

The application of statistics is pervasive in almost all human and scientific endeavours. It is therefore of vital importance that all people who wish to further their knowledge of statistical methodology be able to combine a strong theoretical foundation with practical applications of current techniques employed by professionals in industry, research and teaching. We aim to help people learn and apply statistical modelling to physical, biological, sporting and economic phenomena. This will enable them to be contribute to applied research and development in industry, commerce and research. Particular emphasis is placed on the acquisition and analysis of data using computer-based technology. Our expertise includes all facets of data analysis, design and analysis of experiments, forecasting, quality control, quality assurance, capability analysis, statistical inference, game theory applications and queuing theory. We also have a strong focus on promoting the scholarship of learning and teaching in statistics education. We are dedicated to building the statistical capacity of our graduates, industry partners and wider community.

Dr Mali Abdollahian [email protected]

Research activities

Our problem-solving approach contributes to innovative and outcome-driven research in a broad ranges of areas across academia, government and industry.

Grants (2014 -)

• Virtualising Science: Using an Online World to Immerse Junior Secondary School Students in Real Applications of Maths and Science Curriculum. Funded by: DIICCSRTE Office for Learning and Teaching (OLT) Grants 2014 from (2014 to 2016)
• Near Miss Grant (RMIT University, P. Zeephongsekul, $25,000 , 2015).
• Robust Algorithms for an Open Source Software Reliability Tool (NSF, Principal Investigator Dr. L. Fiondella, $124,999, 2015 – 2017).
• New statistical approaches for analysing foodwebs and species distributions. (ARC Discovery, Chief Investigators Lewi Stone, Ascelin Gordon, Yan Wang, $295,900 ,2015 – 2017, $295,900)

Industry research projects

• Badminton Australia. Prediction of Commonwealth and Olympic Games qualification and athlete performance analytics.
• Victorian Institute of Sport (VIS) and Melbourne Vixens. Ball tracking, game analysis and data collection for performance analytics for the Vixens. Statistical analysis of Women’s Olympic Pistol Shooting and ongoing collaboration with Wheelchair Rugby Australia.
• Australian Institute of Sport (AIS)
• AFL. Various projects investigating the impact of injury on interchange and match outcomes and travel and fatigue effects
• ProWess Sports: Beginning in 2007, RMIT and Prowess have undertaken a number of collaborative projects, including Phases of play, interchange analysis and link plays.
• Ulin Hospital (RSUD Ulin) Banjarmasin Indonesia and Department of Mathematics Lambung Mangkurat University, Banjararu, Indonesia. Developing strategies for reducing new borne mortality rate in Indonesia.
• City West Water Corporation. The proposal and development the methodologies for designing economical sampling plans to assist City West Water’s annual sampling strategy to comply with the Australian Standard.
• Fonterra New Zealand. Designing multivariate quality control procedures and optimum regime for the calibration of their lab machines.
• St. Vincent’s Hospital ICU department in Melbourne, Australia. Monitoring patient’s progress after cardiac surgery through multivariate control procedures.
• Australian Pine Timber industry. Controlling the inaccuracies of the timber grading and controlling quality of timber from one batch to another.
• Heinz Food Processing Company. Designing an optimal quality assurance scheme for sampling inspection and quality auditing using the national quality assurance guidelines.
• National Electrical Contractors Association. Survey and analysis work to determine the health and safety of workers.
• Electrical Regulatory Authorities Council. Development and assessment of an online tool used to determine the risk of products for the consumer market.
• VTAC. Statistical analysis and advice for a report assessing the value of moving VTAC to improve accessibility to the wider community.
• Barwon Health, Geelong Hospital. Investigating predictors of post-operative survival in elderly populations.
• National Hospital of Pediatrics, Hanoi, Vietnam. Establishing reference intervals for the diagnosis of neuroblastoma in Vietnamese children. This work has been published in the journal Clinical Biochemistry.
• Victorian Association for the Care and Resettlement of Offenders (VACRO). Analysis of internal survey data used to guide strategic decision making.
• Victorian Legal Aid. Analysis of survey data and general statistical advice for internal reporting purposes.

Academic staff

• Dr Mali Abdollahian
• Dr Arathi Akala
• Dr James Baglin
• Associate Professor Cliff Da Costa
• Dr Anil Dolgun
• Emeritus Professor Kathy Horadam
• Dr Stelios Georgiou
• Dr Andrew Stacey
• Dr Stella Stylianou
• Dr Yan Wang

Current HDR candidates (2014-)

• Dewi Anggraini - Development of Multivariate Quality Control and Assurance Models for Antenatal Care Service in Indonesia (PhD).
• Aaron Corris - Development and Evaluation of Statistical Models to Predict Match Results (Masters by Research).
• Michael De Lorenzo - Evaluating the Importance of Games in Professional Sports and the Effect on Team and Player Performance (PhD).
• Nadeera Gunaratne – Multivariate Process Variability Monitoring (PhD)
• Jason Hunt - Linking spatial Movement with In-Play Data (PhD).
• Gabriel Deng Makuei – Performance Evaluation of the Procedures Aimed at Reducing maternal Mortality Rate in South Sudan (PhD).
• Minh Huynh - Bringing the Island to schools Improving student attitudes towards statistics (PhD).
• Bradley O’Bree - Mathematical Modelling in Professional Golf and Ice Hockey Prediction of Player Performance and Simulation of Tournament and Match Outcomes (PhD).
• Osama Alamri-A Service Level Agreement Based on Multiple Customers in a Supply Chain (PhD).
• Jong Ho Park - Basketball prediction modelling (PhD).
• Vira Koshkina – Species distribution modelling (PhD).

Past HDR candidates (2013- )

• Nipun Agarwal- Psychological Pricing in Mergers and Acquisitions, 2013 (Masters by Research).
• James Baglin - Evaluating Learning Theory-based Methods for Improving the Learning Outcomes of Introductory Statistics Courses, 2014 (PhD).
• Raymond Bedford – From Seabed to Management – a Whole System Model, 2015 (PhD).
• Chathuri L. Jayasinghe - Nonparametric Approach to Reliability and its Applications, 2013 (PhD).
• Michelle Viney - Prediction of In-Play Tennis, 2015, (PhD).
• Ummul Fahri Abdul Rauf – A Copula-based Analysis of Flood Phenomena in Victoria, Australia, 2014 (PhD).
• Xu Zhang – Game Theoretical Approach in Supply Chain Management, 2014 (PhD).

Collaborators and External Members

• Dr. Lance Fiondella, University of Massachusetts, Dartmouth, USA.

Undertake a research degree

Prospective Higher Degree by Research applicants should contact one of our academic or post-doc members to discuss supervision of a research project.

Related research degrees

• PhD (Mathematical Sciences)
• Master of Science (Mathematical Sciences)

Acknowledgement of Country

RMIT University acknowledges the people of the Woi wurrung and Boon wurrung language groups of the eastern Kulin Nation on whose unceded lands we conduct the business of the University. RMIT University respectfully acknowledges their Ancestors and Elders, past and present. RMIT also acknowledges the Traditional Custodians and their Ancestors of the lands and waters across Australia where we conduct our business - Artwork 'Luwaytini' by Mark Cleaver, Palawa.

RMIT University acknowledges the people of the Woi wurrung and Boon wurrung language groups of the eastern Kulin Nation on whose unceded lands we conduct the business of the University. RMIT University respectfully acknowledges their Ancestors and Elders, past and present. RMIT also acknowledges the Traditional Custodians and their Ancestors of the lands and waters across Australia where we conduct our business.

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Postgraduate Research Scholarship in Mathematics and Statistics

A postgraduate research scholarship

University of Sydney RTP rate stipend for a Masters by Research or PhD student to conduct research in mathematics (applied/pure) and statistics.

How to apply

Research students within the Faculty of Science applying for the Research Training Program (RTP) scholarship will automatically be considered for this scholarship. A separate application is not required.

To be considered for this scholarship, you must have applied for the RTP Scholarship ( domestic / international ) for the relevant research period.

The Scholarship will provide a stipend allowance equivalent to the University of Sydney Research Training Program (RTP) Stipend rate (indexed on 1 January each year). The duration of the scholarship is as follows, subject to satisfactory academic performance:

 I.            up to 1.75 years for a successful Masters by Research,

 II.            up to 3 years for a successful PhD recipient.

The PhD recipient encouraged to complete their PhD in 3 years but may apply for an extension of the primary stipend allowance for up to 6 months.

Student Services Amenities fee (SSAF) are also provided for a successful applicant. The duration of the scholarship is as follows, subject to satisfactory academic performance:

I.            up to seven research periods for a successful Masters by Research recipient,

II.            up to twelve research periods for a successful PhD recipient with a possible extension for up to two research periods. 

Who's eligible

• have an unconditional offer of admission or be enrolled in a full-time Masters by Research or PhD at the Faculty of Science
• be willing to conduct research with the School of Mathematics and Statistics
• apply and be considered for the Research Training Program (RTP) Stipend Scholarships
• not be in receipt of an RTP, Universty of Sydney Postgraduate Award (UPA) or equivalent primary scholarship.

This Scholarship has been established to provide financial assistance to Masters by Research or PhD students who are undertaking research in mathematics (applied/pure) and statistics.

Terms and conditions

1. Background

a. This Scholarship has been established to provide financial assistance to Masters by Research or PhD students who are undertaking research in mathematics (applied/pure) and statistics.

b. This Scholarship is funded by the School of Mathematics and Statistics.

2. Eligibility

a. The Scholarship is offered subject to the candidate having an unconditional offer of admission or being currently enrolled to study full-time in a Masters by Research or PhD within the School of Mathematics and Statistics, Faculty of Science at the University of Sydney.

b. Candidate must be willing to conduct research with the School of Mathematics and Statistics.

c. Candidate must apply and be considered for the Research Training Program (RTP) Stipend Scholarships.

d. Candidate cannot be in receipt of an RTP, University of Sydney Postgraduate Award (UPA) or equivalent primary scholarship.

3. Selection Criteria

a. The successful applicant will be awarded the Scholarship on the basis of:

I. academic merit, II. area of study and/or research proposal, III. curriculum vitae, IV. previous research experience, which includes relevant professional experience, scholarly publications and other relevant research output.

b. The successful applicant will be awarded the Scholarship on the nomination of the Associate Head Research Education and the Deputy Associated Head Research Education in the School of Mathematics and Statistics.

a. The Scholarship will provide a stipend allowance equivalent to the University of Sydney Research Training Program (RTP) Stipend rate (indexed on 1 January each year). The duration of the scholarship is as follows, subject to satisfactory academic performance:

I. up to 1.75 years for a successful Masters by Research, II. up to 3 years for a successful PhD recipient.

b. The PhD recipient encouraged to complete their PhD in 3 years but may apply for an extension of the primary stipend allowance for up to 6 months.

c. Student Services Amenities fee (SSAF) are also provided for a successful applicant. The duration of the scholarship is as follows, subject to satisfactory academic performance:

I. up to seven research periods for a successful Masters by Research recipient, II. up to twelve research periods for a successful PhD recipient with a possible extension for up to two research periods.

d. Periods of study already undertaken towards the degree prior to the commencement of the Scholarship will be deducted from the maximum duration of the Scholarship excluding the potential extension period.

e. The Scholarship is for commencement in the relevant research period in which it is offered and cannot be deferred or transferred to another area of research without prior approval.

f. No other amount is payable.

g. The Scholarship will be offered subject to the availability of funding.

5. Eligibility for Progression

a. Progression is subject to attending and passing the annual progress evaluation.

6. Leave Arrangements

a. The Scholarship recipient receives up to 20 working days recreation leave each year of the Scholarship and this may be accrued. However, the student will forfeit any unused leave remaining when the Scholarship is terminated or complete. Recreation leave does not attract a leave loading and the supervisor's agreement must be obtained before leave is taken.

b. The Scholarship recipient may take up to 10 working days sick leave each year of the Scholarship and this may be accrued over the tenure of the Scholarship. Students with family responsibilities, caring for sick children or relatives, or experiencing domestic violence, may convert up to five days of their annual sick leave entitlement to carer’s leave on presentation of medical certificate(s). Students taking sick leave must inform their supervisor as soon as practicable.

7. Research Overseas

a. The Scholarship recipient may not normally conduct research overseas within the first six months of award.

b. The Scholarship holder may conduct up to 12 months of their research outside Australia. Approval must be sought from the student's supervisor, Head of School and the Faculty via application to the Higher Degree by Research Administration Centre (HDRAC) and will only be granted if the research is essential for completion of the degree.

c. All periods of overseas research are cumulative and will be counted towards a student's candidature. Students must remain enrolled full-time at the University and receive approval to count time away.

8. Suspension

a. The Scholarship recipient cannot suspend their award within their first six months of study, unless a legislative provision applies.

b. The Scholarship recipient may apply for up to 12 months suspension of the Scholarship for any reason during the tenure of the Scholarship. Periods of Scholarship suspension are cumulative and failure to resume study after suspension will result in the award being terminated. Approval must be sought from the student's supervisor, Head of School and the Faculty via application to the Higher Degree by Research Administration Centre (HDRAC). Periods of study towards the degree during suspension of the Scholarship will be deducted from the maximum tenure of the Scholarship.

9. Changes in Enrolment

a. The Scholarship recipient must notify HDRAC and their supervisor promptly of any planned changes to their enrolment including but not limited to: attendance pattern, suspension, leave of absence, withdrawal, course transfer, and candidature upgrade or downgrade. If the award holder does not provide notice of the changes identified above, the University may require repayment of any overpaid stipend and/or tuition fees.

10. Termination

a. The Scholarship will be terminated:

I. on resignation or withdrawal of the recipient from their research degree, II. upon submission of the thesis or at the end of the award, III. if the recipient ceases to be a full-time student and prior approval has not been obtained to hold the Scholarship on a part-time basis, IV. upon the recipient having completed the maximum candidature for their degree as per the University of Sydney (Higher Degree by Research) Rule 2011 Policy, V. if the recipient receives an alternative primary stipend and/or tuition fee scholarship. In such circumstances this Scholarship will be terminated in favour of the alternative stipend and/or tuition fee scholarship where it is of higher value, VI. if the recipient does not resume study at the end of a period of approved leave, or VII. if the recipient ceases to meet the eligibility requirements specified for this Scholarship, (other than during a period in which the Scholarship has been suspended or during a period of approved leave).

b. The Scholarship may also be terminated by the University before this time if, in the opinion of the University:

I. the course of study is not being carried out with competence and diligence or in accordance with the terms of this offer, II. the student fails to maintain satisfactory progress, or III. the student has committed misconduct or other inappropriate conduct.

c. The Scholarship will be suspended throughout the duration of any enquiry/appeal process.

d. Once the Scholarship has been terminated, it will not be reinstated unless due to University error.

11. Misconduct

a. Where during the Scholarship a student engages in misconduct, or other inappropriate conduct (either during the Scholarship or in connection with the student’s application and eligibility for the Scholarship), which in the opinion of the University warrants recovery of funds provided, the University may require the student to repay payments made in connection with the Scholarship. Examples of such conduct include and without limitation; academic dishonesty, research misconduct within the meaning of the Research Code of Conduct 2023 (for example, plagiarism in proposing, carrying out or reporting the results of research, or failure to declare or manage a serious conflict of interests), breach of the Student Charter 2020 and misrepresentation in the application materials or other documentation associated with the Scholarship.

b. The University may require such repayment at any time during or after the Scholarship period. In addition, by accepting this Scholarship, the student consents to all aspects of any investigation into misconduct in connection with this Scholarship being disclosed by the University to the funding body and/or any relevant professional body.  

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39 Best universities for Statistics in Australia

Updated: February 29, 2024

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Below is a list of best universities in Australia ranked based on their research performance in Statistics. A graph of 13M citations received by 460K academic papers made by 39 universities in Australia was used to calculate publications' ratings, which then were adjusted for release dates and added to final scores.

We don't distinguish between undergraduate and graduate programs nor do we adjust for current majors offered. You can find information about granted degrees on a university page but always double-check with the university website.

1. University of Sydney

For Statistics

2. University of Melbourne

3. University of New South Wales

4. University of Queensland

5. Monash University

6. Australian National University

7. University of Western Australia

8. University of Adelaide

9. Queensland University of Technology

10. University of Technology Sydney

11. University of Newcastle

12. Deakin University

13. Griffith University

14. Macquarie University

15. Curtin University

16. La Trobe University

17. University of Wollongong

18. University of South Australia

19. University of Tasmania

20. Flinders University

21. RMIT University

22. Western Sydney University

23. Swinburne University of Technology

24. James Cook University

25. University of New England, Australia

26. Victoria University

27. University of Canberra

28. Edith Cowan University

29. University of Southern Queensland

30. Murdoch University

31. Central Queensland University

32. Charles Sturt University

33. Australian Catholic University

34. Bond University

35. Charles Darwin University

36. Federation University Australia

37. Southern Cross University

38. University of the Sunshine Coast

39. University of Notre Dame Australia

The best cities to study Statistics in Australia based on the number of universities and their ranks are Sydney , Melbourne , St Lucia , and Clayton .

Mathematics subfields in Australia

• Melbourne School of Population and Global Health
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Centre for Epidemiology and Biostatistics

We are passionate about training and mentoring the next generation of researchers. We offer PhD and MPhil degrees.

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Resources and news.

Our research uses advanced methods in epidemiology, biostatistics, health humanities and social sciences, and our findings seek to significantly influence global public health policy. We share this research and contribute to the community using a range of knowledge transfer activities.

see all the latest resources and research news into COVID-19

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Research Themes

Our research is encompassed within several broad research themes. This multidisciplinary approach aims to increase the opportunities for researchers to collaborate on projects that span common themes.

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An overview of the research interests within the school and the project work being carried out by our research groups.

Graduate Research

We are passionate about the training and mentoring of the next generation of scientists. A range of research degrees are offered at Master and Doctorate level.

Whether you're just starting out or a seasoned professional, we have something to suit your needs and schedule. With the highest teaching evaluations in the Faculty of Medicine, Dentistry and Health Sciences we are proud to offer our coursework and short course programs to our leaders and future leaders.

Our degrees, taught by our world-renowned academics are the perfect way to begin in population and global health.

Short Courses

Our short courses are designed to keep you up to date with the latest research and information.

Single subjects

Single subject study can be a stepping-stone to further qualifications or an upskilling opportunity. Develop knowledge and skills without the commitment of a full course from the School offering of over 50 subjects.

Scholarships, Bursaries and Prizes

The Faculty of Medicine, Dentistry and Health Sciences offer an extensive range of scholarships and bursaries to undergraduate and postgraduate coursework students.

Student Placements

Work-integrated learning, including placement, provides career-defining experiences for students and is integral to many programs within the Faculty of Medicine, Dentistry and Health Sciences.

Find out more

Graduate Research at MSPGH

Interested in completing a PhD or Master of Research at the Melbourne School of Population and Global Health (MSPGH)? Already commenced and looking for help? Visit the Faculty of Medicine, Dentistry and Health Sciences (MDHS) to learn about graduate research degrees, including guides and resources to support students and supervisors from commencement through to completion. Explore information on the application process, scholarships, visas, progress, PhD programs, policies & procedures, professional development and where to go when you need help.

Explore Graduate Research

Thank you for your interest in engaging with the Melbourne School of Population and Global Health. As a friend and supporter of the school, you can support ground-breaking research, help create scholarships for our students, build important partnerships and promote community engagement.

Our pride in our graduates and in their lives spent improving the health and well-being of others is matched by our desire to maintain strong connections with all who have passed through our doors.

We are grateful to our alumni and donors for their help creating scholarships, supporting ground-breaking research, building important partnerships and assisting community engagement.

We recognise partnerships and collaborations are an integral facet of our development and a major strength of the school.

The School aims to be of value to the community through its teaching, research and program implementation.

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PhD in Statistics: Course Details, Eligibility, Admission, Fees

PhD in Statistics is a three to six years long doctorate program that deals with the collection, analysis, interpretation, and presentation of numerical data. This course graduate can get many job roles such as Research Analyst, Assistant Professor, Data Analyst, Biostatistician, Data Interpreter, Lecturer, Research Scholar etc.

PhD Statistics Course Details

About phd in statistics.

PhD in Statistics is a three to six years doctorate which is created in such a way that the learners get to know a deep understanding of their chosen topics. Over the past few years, the scope of pursuing PhD courses in India has increased manifolds. Many universities are in front of admission in this PhD course . 

According to Wikipedia "Statistics is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data. In applying statistics to a scientific, industrial, or social problem, it is conventional, to begin with, a statistical population or a statistical model to be studied."

TABLE OF CONTENTS

• PhD in Statistics Eligibility Criteria
• PhD in Statistics Admission Process
• Who Should Do a PhD in Statistics

Types of PhD in Statistics

• Popular PhD in Statistics Entrance Exams

Study PhD in Statistics in India

• Top PhD in Statistics Colleges
• Study PhD in Statistics in Abroad
• PhD in Statistics Fees Structure
• PhD in Statistics Syllabus and Subjects

Why Choose PhD in Statistics?

Phd in statistics course comparison.

• Scope of Higher Education for PhD in Statistics

Preparation Tips for PhD in Statistics

• Salary of a PhD in Statistics Graduate
• Career Options after PhD in Statistics
• Skills to Excel

Eligibility Criteria for PhD in Statistics

As all the students know how important a PhD in Statistics course is, that’s why it’s quite difficult to get admitted into their respective interested universities. Those students who want to take enrollment in this doctorate program have to qualify for the eligibility criteria i.e one should have a minimum mark of 55% in either MSc or MA in Mathematics or Statistics. 

There are few PhD Agricultural entrance exams such as GATE, CSIR- UGC NET, UGC-NET, and BHU which have cutoffs to qualify. There is no age limit for the students for taking admission to this course.

How To Get Admission for PhD in Statistics?

Admission to the PhD in Statistics course is not impossible if the students ensure that they research the details well. The universities follow the process of entrance-based admissions. The admission process with respect to admission through exams varies from college to college. Online and offline both facilities are available to the students for enrollment. The students are guided to check the college website to get detailed information

How to Apply?

There are two ways to apply for admission in the PhD Statistics course. Either online by visiting the college website and following the steps given there or offline by visiting the university's office. 

There are certain colleges that take interviews for checking the knowledge and communication skills of the candidates.

Selection Process

The selection process of the candidates for getting admission in the respective PhD in Statistics course ends on interview. The students who have cracked the entrance exams with good marks can give interviews for the further joining process. The last step of the admission procedure decides whether the student is eligible to take admission or not.

Who Should Pursue a PhD in Statistics

A PhD in Statistics is a three to six years doctorate program that makes a student’s career in the public, private, academic, and non-profit sectors. When it comes to your career graph. A PhD in Statistics degree gives a variety of job opportunities to the graduates.

One of the most sought-after jobs for a PhD Statistics degree holder is of a lecturer or a professor in a university or a researcher in most fields. 

Along with this, a PhD in Statistics degree holder can get a job in Ecological, Medical, Census, Election, Crime, Education, Film, Cricket, Tourism, Insurance, Statistical Research, Indian Statistical Services, etc. Candidates will have in-depth knowledge and develop mastery over the subjects they have chosen for specialization, which will be extremely useful for them in their careers. Those learners who are interested in these specializations should pursue this course.

When to do a PhD in Statistics?

Aspirants are eligible to pursue a PhD in Statistics course only if they have completed their master's degree in a similar course/ field/ stream in which they want to pursue a PhD in Statistics. Some colleges also specify that candidates need to have completed an MPhil to pursue a PhD in Statistics course offered by them.

A PhD in Statistics is a research-based doctorate program and that's the reason this course can be done in any of three modes i.e full-time, part-time, and distance learning mode. Aspirants can pursue the PhD in Statistics course at many top universities. 

Full-Time PhD in Statistics

A full-time PhD Statistics program duration is three to six years that is provided by many top respected colleges or universities. This full-time course is all about classroom-based studying, research projects, and assignments. There are no limitations on the age for taking admissions.

Part-Time PhD in Statistics

A part-time PhD Agricultural program is for 6-10 years. This course is basically created for the students who are working somewhere or are professionals. A part-time mode is all about having limited classes. Part-time PhD is mainly focused on research for the development of the company rather than individual research work.

Distance PhD in Statistics

A distance PhD in Statistics in India program is quite easy for getting knowledge at any time from anywhere. Many people believe in pursuing this course because of no issue of being physically present at the universities. The objective behind the creation of this distance learning program is to provide the degree along with the knowledge while working.

Popular Entrance Exams for PhD in Statistics

Various institutes and testing agencies conduct PhD in Statistics entrance exams for admissions regarding PhD in Statistics and Technology. The following are some of these entrance examinations:

• CSIR- UGC NET

A Quick Glance at the PhD in Statistics Entrance Exams

Students can access the PhD in Statistics course details by going to the college's official website to which they are interested in applying. The specialization plays a vital role in the college's approach to the entrance exam. Below listed are some of the general guidelines of the PhD in Statistics entrance examinations: 

• The exam pattern includes common topics from 10+2, graduation and postgraduation level i.e. technology, life sciences, mathematics, sciences, and general aptitude.
• The papers are objective and MCQ-based.
• The syllabus, mode of examination, and question pattern may change according to a university/conducting body.

India is home to some of the PhD in Statistics colleges in the world. Aspirants have many options to choose from in terms of the best PhD in Statistics course as per their preferences. Depending on the type of PhD Statistics programs offered, candidates will have to make the appropriate choice. Below are some of the top colleges in India offering PhD in Statistics courses:

Top 10 PhD in Statistics Colleges in India

Below is the list of the top best PhD in Statistics colleges in the country:

Top PhD in Statistics Colleges in New Delhi

Delhi, the educational hub of India, stands in the fourth position in producing PhD in Statistics candidates. Here are the top 5 PhD in Statistics Colleges in New Delhi:

Top PhD in Statistics Colleges in Chennai

The top 5 PhD in Statistics Colleges in Chennai are given below:

Top PhD in Statistics Colleges in Pune

Below is the list of colleges which are the top colleges for PhD in Statistics in Pune:

Top PhD in Statistics Colleges in Bangalore

Banglore city has some of the best colleges for PhD in Statistics courses in India. Here is the list of top colleges for PhD in Statistics in Bangalore:

Top PhD in Statistics Colleges in Kolkata

Check the Table below for the top colleges in Kolkata:

Top PhD in Statistics Colleges in Hyderabad

The Telangana state capital has some premier institutions in the country for PhD in Statistics courses in India. Check the table below for the top PhD Statistics colleges in Hyderabad:

Top PhD in Statistics Government Colleges

There are several top Government Colleges offering quality PhD in Statistics programmes across the country. Check the table below for the top PhD in Statistics government colleges in India:

Top PhD in Statistics Private Colleges

India has seen significant growth in the number of quality PhD in Statistics private colleges that offer some of the best programmes in the country. Check the table below for the top PhD in Statistics private colleges in India:

Study PhD in Statistics Abroad

Students can opt to study a PhD in Statistics course abroad if they can afford it. The PhD Statistics course abroad is up to 5-8 years, depending on the type of course, college and country. 

The benefits of studying a PhD in Statistics course abroad are access to some of the best resources, facilities, and faculties, apart from worldwide exposure in terms of subject matter and other cultures. 

Top PhD in Statistics Colleges Abroad

The table below contains the list of some of the best colleges abroad for PhD in Statistics:

Top PhD in Statistics Colleges in the USA

The USA is home to some of the best universities and colleges offering top-notch PhD in Statistics programmes in the world. The US is the best country for PhD in Statistics studies and settling abroad. It's a PhD Statistics-level that the USA really shines through. The table below contains the list of top colleges of PhD in Statistics in the USA:

Top PhD in Statistics Colleges in the Uk

A PhD in Statistics is a research degree and is the highest award available at universities in the UK. The study is based on a substantial research project on an area of academic interest, typically up to 100,000 words in length, written as a thesis which then must be defended in an oral examination in front of a panel of experts.

The table below contains the list of top colleges of PhD in Statistics in the Uk:

Top PhD in Statistics Colleges in Canada

An increasingly attractive and multicultural study destination, Canada is a great option to consider for your PhD Statistics studies, offering a wealth of research opportunities to help you expand your expertise. Here are the top universities for PhD in Statistics in Canada:

Top PhD in Statistics Colleges in Australia

A PhD in Statistics in Australia means that you will develop your knowledge and skills, which ultimately increases your chances for employment within Australia and in any country. According to the UN's Education Index, Australia's education system ranks first. The table below shows the top universities of PhD in Statistics in Australia:

Top PhD in Statistics Colleges in Germany

It is much easier to get a PhD in Statistics in a European university, which takes about 3-4 years in a good university in Europe. The PhD Statistics from Germany in engineering enjoys an outstanding reputation. Germany's research institutions, universities and companies welcome international researchers and offer excellent opportunities for doctoral students.

The table below shows the top universities in Germany colleges of PhD in Statistics:

Fee Structure for PhD in Statistics

The fee structure for PhD in Statistics varies for different Universities. Also, the fee structure varies following the course and University. Students can download the admission brochure as well as the course curriculum to get the details of PhD Statistics admission and fee structure. 

The average PhD in Statistics fee in India is INR 5,000 - 2 LPA. Now, read below to know about the fee structure of different universities.

Syllabus and Subjects for PhD in Statistics

PhD in Statistics is a doctorate course in Agriculture. The course may have a duration of 2 years and it is a full-time course. It is a research-based course. In the PhD in Statistics duration, the candidates get to learn the collection, analysis, interpretation, and presentation of numerical data. This course mainly covers areas like Math and Statistics, etc. The students come to know about the fundamentals of agriculture and crop production. Though the actual course offerings might differ from one university to another, here is a list of major subjects which are commonly studied under a PhD Statistics:

• Statistical Methods
• Probability Theory
• Vectors and Matrices
• C or C++ Programming
• Numerical Analysis
• Elementary Inference
• Statistical Quality Control
• Mathematical Analysis

Read More: PhD in Statistics Subjects and syllabus

When students decide to pursue the PhD in Statistics qualification, they should research PhD in Statistics course details to ensure that they know the course they are enrolled in. Some of the common queries that students encounter are, "What is PhD Statistics" and "Why PhD Statistics?". To understand the answer to these questions, we can make it simpler by breaking it down into the following three short questions:

What is PhD in Statistics All About?

A PhD in Statistics or Doctor of Philosophy is a doctoral research degree and is normally the highest level of academic qualification one can achieve. A PhD in Statistics degree holder can get a job as Research Analyst, Assistant Professor, Data Analyst, Biostatistician, Data Interpreter, Lecturer, Research Scholar, and many more. 

The course has a specialization that deals with Statistical Methods and Mathematical Analysis. Students need to check the PhD in Statistics course outline perfectly.

What do PhD in Statistics Graduates do?

Students can select the subjects of their choice depending on their interest in job prospects available in the specific field. Since graduates with a PhD Statistics degree possess skills in various subjects, there are career opportunities available in multiple fields for them. 

In addition, there are many responsibilities that graduates of this role have to undertake, which makes the role very dynamic and diverse.

Data Analyst: One of the popular roles undertaken by graduates of the PhD in Statistics course is Data Analyst. Although responsibilities might vary based on position and industry, data analysts are often in charge of gathering data, organizing it, and pinpointing trends and patterns. In the later stages of a project, data analysts produce visualizations and reports and communicate their findings to leadership

Reasons Why PhD in Statistics Can Fetch You a Rewarding Career?

PhD in Statistics courses are a very reflective and exciting stream of education. Students can gauge the intrinsic worth of a PhD Statistics course because it offers more avenues of employment opportunities than any other stream. Thus, the PhD in Statistics job scope is forever widening and appealing.

Diversity in Job roles : There is a diverse range of job roles available for the graduates of this course. Since the specializations available to the students are very flexible, it enables the students to pursue a wide range of roles in their careers.

Read More: PhD in Statistics Jobs & Scope

PhD in Statistics stands for Doctor of Philosophy in Statistics and is typically catered to students interested in and inclined towards research-based degrees and professional application. Here is a course comparison of PhD Statistics with another course:

PhD Statistics vs PhD Agronomy

There are many tips that students must note when deciding to pursue a PhD in Statistics degree. Some important preparation tips are listed below to ensure that the students crack the course and pass the exams without any hurdles. 

Improve Vocabulary:  Improving vocabulary is very necessary as the PhD in Statistics course deals with many writing and reading activities. So having excellent communication and writing skills are a plus for the student studying the PhD in Statistics course.

Read and Practice More: Being up to date with the syllabus every day is very important. Practising and reading more will help the student be thorough with the syllabus and do well in the exams.

Have Intrinsic Knowledge and Interest in Subjects: Having intrinsic knowledge about the subject and having the same interest will keep the student motivated to learn more than what's in the syllabus.

Revise Methodically: Revising from time to time can be a key to scoring well in the final exam. Keep revising regularly and understand the subject properly. Revision is the key to scoring good marks.

Salary of a PhD in Statistics Graduates

The salary depends on the kind of job you get/you choose to do, what your PhD in Statistics research area is and where you are employed.No prior experience is required to be a PhD in Statistics Student. The average Salary of a PhD in Statistics graduate starts from INR 3 - INR 8 LPA (Source: Payscale), depending on the stream you belong from.

Read More: PhD in Statistics Job Salary

Career Options After PhD in Statistics

A PhD in Statistics degree is pursued by a majority of students because it offers better career options, for example, in the field of academics and research. PhD in Statistics in itself is a broad term, it has many specializations that have different career options and jobs. PhD Statistics Jobs include:

• Senior Data Science Researcher
• Life science Teaching Faculty
• Quantitative Research Scientist
• Associate Research Scientist, Human Biology
• Dolat Capital - Quantitative Research Scientist
• Research Scientist

Skills That Make You The Best PhD in Statistics Graduates

For studying a course like PhD in Statistics, there are so many skills that a student needs to have. The skills help the students to get well-maintained dignity, respect, and so much attention. 

So, that’s why the students need to put their efforts to come out of their comfort zones and earn respect as much as possible. Some of these skills include:

• Academic Ability
• Accountability
• Persistence
• Good Communication Skills
• Time Management
• Open-mindedness and Curiosity to Learn Something New
• Ability to Think

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PhD scholarships in statistical machine learning, University of Wollongong, Australia

Nov 6, 2023

University of Western Australia, Australia

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University of Lancaster, UK

PhD Scholarships are available in the area of statistical learning with applications to metocean and ocean engineering. Research topics in statistical learning identified as PhD projects include (1) sequential decision making and optimal design to augment targeted and efficient data acquisition; (2) data driven spatio-temporal inference/prediction of complex ocean dynamic processes; (3) statistical analyses, emulation, and uncertainty quantification of physical models.

The student will be a member of the Australian Research Council’s (ARC) Industrial Transformation Research Hub for Transforming energy Infrastructure through Digital Engineering (TIDE), situated in the Indian Ocean Marine Research Centre (IOMRC) at the University of Western Australia (UWA). TIDE brings together a vibrant international team of researchers in statistics, data science, and ocean engineering. The data science team within the Hub is comprised of researchers located at the University of Western Australia, University of Wollongong, Australia, and University of Lancaster, UK, with expertise in statistics, machine learning, and applied mathematics. Successful applicants will be hosted at one of the aforementioned institutions, depending on research interests and student circumstances, and will engage in collaboration across, and travel between, institutions.

A generous scholarship will be made available to fund the student’s studies for three years full-time. An additional top-up scholarship is also available for outstanding candidates. Tuition fees for outstanding international students (for up to 4 years) will be waived. The successful applicant will have the opportunity to work with both Australian and international collaborators, and funding is available for conference travel.

Applications are invited from domestic and international students who are able to commence their PhD studies in early 2024. Applicants should hold, or be close to completing, an Honours undergraduate degree or a Masters degree in Statistics, Machine Learning, or a closely related field. The ideal candidate will have an interest in the development of statistical learning/machine learning methodology and computation, excellent mathematical and programming skills, and an interest in using them to model and predict environmental or engineering phenomena. Self-motivation, strong research potential, and good oral and written communication skills are essential criteria.

To apply, please send in academic transcripts, a CV, and a cover letter outlining your motivation for conducting research in one of the above areas to Kath Lundy ([email protected]). For informal queries, please contact A/Prof. Andrew Zammit Mangion ([email protected]), A/Prof. Edward Cripps ([email protected]) or Prof. David Leslie ([email protected]).

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• Research in specialist sport and exercise medicine training
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• Bruce Hamilton 1 , 2 ,
• http://orcid.org/0000-0002-8413-2814 Larissa Trease 3 , 4 ,
• Corey Cunningham 4 , 5
• 1 Sports Medicine , High Performance Sport New Zealand AUT Millennium Institute of Sport and Health , Auckland , New Zealand
• 2 SPRINZ , Auckland University of Technology , Auckland , New Zealand
• 3 La Trobe Sport and Exercise Medicine Research Centre (LASEM) , La Trobe University , Bundoora , Victoria , Australia
• 4 Australasian College of Sport and Exercise Physicians , Melbourne , Victoria , Australia
• 5 New South Wales Institute of Sport , Sydney Olympic Park , New South Wales , Australia
• Correspondence to Dr Bruce Hamilton, Sports Medicine, High Performance Sport New Zealand AUT Millennium Institute of Sport and Health, Auckland, New Zealand; bruce.hamilton{at}hpsnz.org.nz

https://doi.org/10.1136/bjsports-2024-108554

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• Sports medicine

Over 20 years ago, Thomas Best and Domhnall MacAuley rhetorically posited that evidence-based sports medicine was potentially a ‘contradiction in terms’. 1 In 2010, Evert Verhagen and Willem van Mechelen stated that ‘most individuals involved in sports medicine are not thoroughly trained in epidemiological and methodological rigour’. 2 Despite these somewhat disparaging views, research has long been recognised as an important component of specialist training in sport and exercise medicine, 3 4 at least in part as a result of academic medical centres demonstrating better patient outcomes. 5 Indeed, the Australasian College of Sport and Exercise Physicians (ACSEP) has centralised the role of research in sports medicine training since its inception in 1985, incorporating a requirement to complete original research as part of fellowship training. 6 Until 2023, in order to graduate from the training programme, registrars were required to complete a series of mandatory research modules and undertake ‘an original research project, and [be] published as first author in an international refereed journal’. 7

As part of an internal 2022 review of the college’s research requirements, several limitations with this research approach were identified including:

A focus on publication in a high-level journal as a binary outcome, rather than the process of research.

Inconsistency with the research requirements with other specialist training programmes in Australia and New Zealand. 8

A reliance on the nuances and publication imperatives of academic journals to determine registrar research outcomes, with resultant delays, difficulties in publishing and an inability to complete the fellowship requirements.

A lack of focus on identifying and developing research competencies.

A lack of access for registrars to research environments, resources and technical capability.

Registrar dissatisfaction, frustration and disengagement with research activities.

The review highlighted a conflict between the desirability of incorporating research requirements into specialist sports medicine training, and the unavoidable challenges of performing quality research. Reflecting this, the Medical Council of New Zealand specifically highlights the importance of ‘enquiry, intellectual curiosity and evidence-based practice’ in specialist training, but also acknowledges that ‘not all trainees will have the inclination, opportunity or aptitude for an extended period of research activity’. 9

Following the 2022 review, the ACSEP ‘doubled down’ on its desire to develop specialists who were competent in critically interpreting, applying and undertaking sports medicine research. While recognising that trainee approaches to research engagement may vary, all trainees are required to contribute to or lead a research study. 8 In essence, the college recognised that while not all specialist sport and exercise registrars were destined to be researchers, all specialists must be able to engage positively in research activity. One size does not fit all. Subsequently, the college overhauled the training programme approach to research with the goal of achieving greater research engagement from both registrars and fellows.

In 2023, the ACSEP formally evolved its training requirements to a competency-based assessment with the removal of the singular publication outcome requirement and providing a range of means by which registrars could complete their individualised ‘research-based activity (RBA)’. While the participation in original research remained a requirement, evidence of developing research competencies such as the formulation of research questions and hypotheses, literature reviews and the development of a research methodology allowed registrars to establish a broad research portfolio in order to complete the training requirements. Furthermore, evidence of ongoing involvement in research and the demonstration of the translation of novel research in sporting or clinical environments can contribute to a registrar’s RBA portfolio.

In recognition of the constraints many registrars face in linking with effective research environments and supervisors, the ACSEP has recruited a technical advisor to support registrars in developing appropriate projects and to guide them towards national and international research support networks. Finally, the college has committed to promoting research from its registrars and fellows with a view to ensuring the ongoing involvement in research is seen as a viable and rewarding professional pathway for sport and exercise physicians.

For the specialty of sport and exercise medicine to thrive requires highly skilled and informed clinicians who are able to interpret and use a broad range of 21st century research techniques. In modernising its research curriculum, the ACSEP hopes to be at the forefront of clinical and evidence-based sports medicine in the decades to come. Evidence-based sports medicine should not be a contradiction.

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• MacAuley D ,
• Verhagen E ,
• van Mechelen W
• Humphries D ,
• Dijkstra HP , et al
• Khullar D ,
• Orav EJ , et al
• Brukner PD ,
• Crichton KJ ,
• Stehlik P ,
• Brandenburg C , et al

X @DrLarissaTrease

Contributors All authors contributed to the development of this editorial.

Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

Competing interests CC is the president of the Australasian College of Sport and Exercise Physicians (ACSEP) and BH is the chair of the Research Committee of ACSEP.

Provenance and peer review Not commissioned; externally peer reviewed.

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