Would you like to help us make EURAXESS even better? Take this very quick user satisfaction survey - it won’t take more than 5 minutes!
Organisation/Company Swansea University Department Central Research Field Computer science Physics Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country United Kingdom Application Deadline 20 Aug 2025 - 23:59 (Europe/London) Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 1 Oct 2025 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No
Offer Description
The primary objective of this project is to establish the evidence base on professional cycling road ‘racing’ trends and the critical tactical moments that determine how races are won. This evidence will inform future race strategy and live race tactics.
Multiple factors influence the strategy and tactics in professional road cycling, and these have changed significantly since the COVID-19 pandemic. Some of these factors include the course design, environmental factors, the peloton strength, interaction of team strategies, rider skills, and underlying physiological capabilities in the final critical moments. All these factors are highly dynamic in the way they interact to impact racing tactics and trends.
The specific objectives include:
- Historical analysis of racing from the past 3-5 years across Grand Tours, one-day races (monuments and semi-classics), and select World Tour 1-week stage races. The data sources will include video and previous race commentary to ‘code’ key events in races that help define observable events based on expert knowledge and available evidence.
- Development of a post-race analysis structure, process and data ‘toolkit’ that can build on historical understanding of race trends to provide immediate post-race feedback to Sport Directors that can be used to assess race strategy and tactics.
- Research, review and develop models based on objectives 1 and 2 to develop a race prediction model for stage racing that can be used to inform live race decisions based on emerging events.
The successful candidate will also spend time embedded in a professional cycling environment and gain significant experience in hands-on data collection, data analysis, data presentation and interpretation.
English Language: IELTS 6.5 Overall (5.5+ each comp.) or Swansea University recognised equivalent. Full details of our English Language policy, including certificate time validity, can be found here .
If you have any questions regarding your academic or fee eligibility based on the above, please email pgrscholarships@swansea.ac.uk with the web-link to the scholarship(s) you are interested in.
Specific Requirements
Open to UK fee-eligible Students Only
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
PhD: Applicants must hold a 2.1 (or above) in Mathematics, Physics, Computer Science, or Sport Science. It would be desirable for candidates to have experience in some or all of the following:
- Experience in working or competing in professional sports environments, especially road cycling, to have a grasp of the nature of the sport
- Data visualization solutions (i.e. Power BI, Tableau, Google Data Studio) for producing reports
- MATLAB/PYTHON/R/C programming
- Application of Machine Learning Algorithms
Additional Information
This scholarship covers the full cost of tuition fees, an annual stipend at UKRI rate (currently £20,780 for 2025/26 and a minimum additional top up of £3000 per annum.
Additional research expenses of up to £1,000 per year will also be available.
Eligibility criteria
Open to UK fee-eligible Students Only
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
PhD: Applicants must hold a 2.1 (or above) in Mathematics, Physics, Computer Science, or Sport Science. It would be desirable for candidates to have experience in some or all of the following:
- Experience in working or competing in professional sports environments, especially road cycling, to have a grasp of the nature of the sport
- Data visualization solutions (i.e. Power BI, Tableau, Google Data Studio) for producing reports
- MATLAB/PYTHON/R/C programming
- Application of Machine Learning Algorithms
Please see our website for further information
#J-18808-Ljbffr
