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Fully Funded Swansea University and Swim Wales PhD Scholarship: The Application of Advanced Data Analytics to Monitor Physical Performance Metrics to Enhance the Prediction of Success in International Swimming

Swansea University - Sport and Exercise Sciences

Qualification Type: PhD
Location: Swansea
Funding for: UK Students
Funding amount: £18,622 p.a.
Hours: Full Time
Placed On: 8th December 2023
Closes: 28th February 2024

Funding provider: Swansea University's Faculty of Science and Engineering and Swim Wales

Subject areas: Sport and Exercise Science, Computer Science, Data Science, Mathematics

Project start date: 

  • 1 April 2024 (Enrolment open from mid–March) 
  • 1 July 2024 (Enrolment open from mid-June) 

Project description: 

This PhD project presents a unique opportunity for an individual to pave the way for next generation analysis and visualisations within an elite sporting environment. The candidate will work closely with performance practitioners at Swim Wales, scientists at Swansea university and elite athletes to optimise the performance of competitors through a 4-year Olympic and commonwealth game cycle. 

The aim of this PhD project is to identify opportunities to improve the overall performance of international swimmers through investigating and enhancing the application of advanced data analytics techniques to physical performance data collected by the Swim Wales Sports Science and Sports Medicine Team. Swim performance is comprised of multiple inter-relating factors; such as the athletes physiological output, strength and power, technique and drag coefficient. Developing and analysing these data streams alongside regular training data will form the basis of the project.   

Adequate training loads promote favourable physical and physiological adaptations, reduce the likelihood of illness and injury, and, therefore, increase the possibility of success. Collecting internal and external training load information has become a critical issue in elite sport practice and research. In this regard, monitoring athletes’ global training load is essential for understanding whether an athlete is positively adapting to their training programme. Vast volumes of training, testing and competition data are currently routinely gathered using an array of cameras and on-body sensors to give performance staff an insight into the overall performance process. However, these data streams are typically analysed and reported in isolation, limiting the impact and insight that they can yield. This project will therefore review the current data streams and develop specific data analytics processes to better synthesise and enhance the value that they yield. These will be evaluated by retrospectively establishing their efficacy in performance prediction, with a view to then using them to prospectively inform training design.  

The successful candidate will be embedded within the Swim Wales Sports Science and Sport Medicine team in a high-performance sport environment. They will be responsible for collecting multi-channel data from a range of devices that assess physical and competition performance, will monitor training load, and will ultimately oversee data quality, provenance, and curation within a standardised database. 

Eligibility

Candidates must hold an undergraduate degree at 2.1 level in Sport and Exercise Science, Data Science, Computer Science, Mathematics, or closely related discipline. If you are eligible to apply for the scholarship (i.e. a student who is eligible to pay the UK rate of tuition fees) but do not hold a UK degree, you can check our comparison entry requirements. Please note that you may need to provide evidence of your English Language proficiency. 

Due to funding restrictions, this scholarship is open to applicants eligible to pay tuition fees at the UK rate only, as defined by UKCISA regulations.

Additional Funding Information

This scholarship covers the full cost of UK tuition fees and an annual stipend at UKRI rate (currently £18,622 for 2023/24).

Additional research expenses will also be available.

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