Scholarship details
Application dates
- Applications close
- 30 September 2024
What you'll receive
- You'll receive a stipend of $41,600 per annum for a maximum duration of 3.5 years while undertaking a QUT PhD. The duration includes an extension of up to six months (PhD). This is the full-time, tax exempt rate which will index annually.
- You will receive a tuition fee offset/sponsorship, covering the cost of your tuition fees for the first four full-time equivalent years of your doctoral studies.
- As the scholarship recipient, you will have the opportunity to work with a team of leading researchers, to undertake your own innovative research in and across the field.
- PhD students will receive $20,840 in allowances (training, travel, thesis).
Eligibility
- You need to meet the entry requirements for a QUT Doctor of Philosophy, including any English language requirements.
- Enrol as a full-time, internal student (unless approval for part-time and/or external study is obtained).
- You must be an Australian or New Zealand citizen, Australian permanent resident, or a person entitled to stay in Australia, or enter and stay in Australia, without any limitation as to time.
How to apply
If you are (will be) a graduate (recently or otherwise) from any discipline, complete an expression of interest (EOI). The steps are:
- Complete the EOI available at Next Generation Graduates Program (NGGP): Sports Data Science & AI - Centre for Data Science (qut.edu.au)
- Peruse the projects on offer at Next Generation Graduates Program (NGGP): Our Projects - Centre for Data Science (qut.edu.au). Those that have already been awarded have a student name listed against them.
- Email your top three project preferences, along with your CV and academic record, to admin.sportsdata@qut.edu.au. We will be in touch with next steps.
About the scholarship
Theme
Complex systems modelling
Sports research objectives/questions
In sports like rugby, training is monitored carefully by sports scientists, such that risks to injury can be reduced. In game time, performance is less constrained, heightening the risks that players might endure physical load at higher levels of risk. There is little understanding of how available data might be used to provide better information on individual player loads during a game.
- How to mitigate risk of injury in a game by identifying a real-time measure of cumulative physical load.
- What are the key contributing factors in physical load?
- To what extent does a physiological baseline combined with cumulative physical load contribute to adverse outcomes?