CSIRO & GolfSpace Sports Data Science & AI PhD Scholarship
Value
- Stipend of $42,483 (pa). This is tax-free.
- Training budget: $5,000 (total). This is total across the whole PhD.
- Travel budget: $5,000 (total). This is total across the whole PhD (although students can apply for additional UTS postgraduate travel and research funding).
- Thesis allowance: $840;
- 6-month industry partner placement.
- Integrated training led by the CSIRO on AI and Emerging Technology.
- The CSIRO Sports Data Science and AI Consortium also offers the ability for each of these three students to tap into expertise within other consortium projects across other university partners, including QUT, UNSW and LaTrobe University, and the travel budget supplied can be used to work face-to-face with consortium members (both students and supervisory staff).
Duration
3.5 years
Status
Open
Opens
07/10/2024Closes
01/12/2024Overview
The Human Performance Research Centre and Data Science Institute are seeking one candidate to undertake a Doctor of Philosophy at the Faculty of Health, University of Technology Sydney (UTS) in Sports Data Science with GolfSpace.
CSIRO Sports Data Science and AI Consortium
As part of the Australian Government’s Digital Economy Strategy and Artificial Intelligence Action Plan, the CSIRO, has developed the Next Generation Artificial Intelligence (AI) and Emerging Technologies (ET) graduates’ program. As a part of these initiatives, CSIRO has constructed the “Sports Data Science and AI Consortium.” This consortium aims to train a cohort of future sports data scientists. PhD candidates in this consortium will receive the opportunity to undertake an 11-week coursework program - developed, led, and managed by CSIRO Data61 - allowing students from a diverse range of backgrounds to learn from each other developing foundational skills required for a career in data. Students will also connect with partner institutions during their candidature, allowing them to gain experience in the practical implications of their work.
The Project
UTS, in partnership with GolfSpace, is offering a CSIRO Sports Data Science and AI Consortium PhD opportunity focused on innovative methods for benchmarking, coaching, and practice within the sport of golf. This project presents a unique opportunity to advance the sport by enhancing performance metrics, optimising coaching methods, and developing data-driven practice strategies. The research will explore key questions such as “How do we prepare for the future of golf performance?”, “What factors contribute to a successful practice environment?”, and “How can we use AI-driven insights to personalise coaching methods and accelerate skill development in golfers?”
The successful applicant will be supervised by an interdisciplinary team with expertise across both sport and data science, drawing from academia and industry.
Who is eligible?
- To be eligible for this scholarship, applicants must be domestic students as per the Higher Education Support Act at the time of award. Under this act, domestic students include:
- Australian citizens,
- Australian permanent residents,
- a person entitled to stay in Australia, or to enter and stay in Australia, without any limitation as to time; or
- a New Zealand citizen.
Selection process
We welcome applicants from a broad range of backgrounds. A background in computer science, software engineering, mathematics or statistics lends itself strongly to this project, but we encourage anyone to apply who has a demonstrated passion for artificial intelligence, data science and software development, including pursuit of projects and training in your own time and outside the traditional academic system.
A candidate with a passion and interest in sport, and an interest in delivering highly-applied partner-focused outcomes is also highly valued.
Applicants will be assessed based on academic merit, previous research experience, research outputs, and alignment with the University's research priorities.
In addition to ensuring you are eligible for admission to UTS, students should contact Dr William Sheehan (william.sheehan@uts.edu.au) to discuss suitability before submitting an Expression of Interest (EOI).
How to apply
Successful candidate is then required to submit an online UTS application for the Sports Data Science & AI PhD along with all required documentation as listed on the website by the 5th of January 2025.
Need more information? Contact...
To discuss the research project and or EOI process, please contact
William Sheehan (william.sheehan@uts.edu.au)
To discuss application requirements, please contact Health.Research.Students@uts.edu.au
Other information
To be eligible for a scholarship, applicants are expected to have a record of excellent academic performance and, preferably, additional relevant research experience and/or peer-reviewed research activity, awards and/or prizes.
Scholarship holders will have the opportunity to undertake industry placements with industry partner(s) of the program within which the student enrols.
Students will complete the coursework component of the Next Generation Graduates Program within the first 12 months of receipt of a scholarship (so that skills from this program can be integrated into their doctoral work).
In addition to ensuring you are eligible for scholarship and admission to UTS, students must submit an Expression of Interest (EOI) to William Sheehan (by email: william.sheehan@uts.edu.au). EOI submission deadline is 1st of December 2024, but if a successful candidate is found earlier recruitment will be suspended.
Your EOI should include:
- A personal statement (750 words maximum) outlining your suitability for undertaking this project, what you hope to achieve by doing this project and your research experience to date.
- Academic curriculum vitae including your qualifications, work and research experience, including:
- Evidence of research output (peer-reviewed publications) demonstrating your capacity to undertake independent research.
- Evidence of prizes, scholarships, and awards (certificates, statements of award).
- Evidence of degrees completed to date.
- Official academic transcripts (undergraduate and postgraduate), including master’s thesis results (if applicable).
Shortlisted candidates should be available for a face-to-face interview between 12th and 20th of December 2024.
