Scholarship details

Study levels


Student type

Future students and Current students


Australian or New Zealand and International

Application dates

Applications open
26 June 2021
Applications close
31 July 2021

What you'll receive

You'll receive:

  • an allowance of AU$30,000 per annum (full-time, fixed rate) for 3 years to support living costs during full-time study
  • consideration for a HDR tuition fee sponsorship, if you're an international student.


To be eligible for this scholarship you must:

Your application  will be assessed against the faculty's Doctor of Philosophy eligibility criteria.

Due to COVID-19 travel restrictions, preference and priority will be given to Australian and New Zealand students and resident international students. However, exceptional international applicants will be considered.

QUT and the Centre for Data Science are committed to equity and diversity among our staff and students, to ensure that we mirror the diversity of the community in which QUT exists. In 2018, this was recognised by QUT receiving a Bronze Award in the inaugural SAGE Athena SWAN gender and diversity program.

Women and Aboriginal and Torres Strait Islander students are encouraged to apply.

The provision of a scholarship is conditional on successful application and admission to the IF49 Doctor of Philosophy course. Eligibility for admission to a research degree is determined by the Graduate Research Centre.

How to apply

To apply for this scholarship, submit the following documents to Dr Paul Wu:

  • CV
  • a cover letter
  • a summary (up to two pages) of your career outlining your experience in data science practice or research
  • contact details of three referees (full name, email, and phone number)
  • full academic transcripts
  • English language results (if required)
  • proof of citizenship.

Please review the eligibility requirements prior to submitting your application.

Applications will close 11:59pm (AEST) 31 July 2021.

If you're shortlisted, you will be invited to interview once applications have closed.

What happens next?

If successful, you will be invited to apply and must be accepted into QUT's Doctor of Philosophy program to receive this scholarship.

How to apply for a research degree

Indicate your interest in this scholarship by nominating Dr Paul Wu as principal supervisor and include the name of this scholarship in the financial details section.


The conditions for retaining the scholarship are set out in the rules of the QUT Postgraduate Research Award (Domestic) or QUT Postgraduate Research Award (International).

The scholarship will be governed by QUTPRA rules, but will only include provisions for 12 weeks paid sick leave and paid maternity leave. The scholarship does not cover relocation expenses.

About the scholarship

The Queensland Academy of Sport (QAS), Australian Institute of Sport (AIS) and QUT Centre for Data Science are partners in a world leading program of research in data science in sports. The mission is to tackle key challenges and support day-to-day decisions in sports and athletic training through innovations at the intersection of data science and the sports, and sports science and sports medicine.  Projects will be undertaken with the core partners and organisations for specific sports, including close interaction with the ‘decision support’ needs of coaches.

What’s in it for you?

  • Opportunity to work closely with real-world data, end-users (including coaches) and sports scientists / sports medicine practitioners in Australia’s high-performance sports network to assist with athlete preparation for World Championships and the Olympics / Paralympics.
  • Opportunity to work with leading researchers in statistics and data science.
  • Access to a community of like-minded data science researchers and practitioners nationally and internationally.

Research projects

Applicants will be invited to apply for one of the following projects:

  1. Predictive modelling of injuries and subsequent injuries given training and competition.
  2. Whole-of-systems modelling for multi-criteria, risk-reward based management of athlete training.
  3. Predictive models of adaptation to training: effects of performance versus fatigue.

Each of these projects will have opportunities to develop new statistical and/or machine learning methods, computational algorithms, and visualisations.

For more information about the scholarship or application process please contact Dr Paul Wu.

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