We’re pleased to highlight an exciting, fully-funded PhD opportunity at Swansea University exploring the cutting edge of performance analysis and tactical decision-making in elite professional cycling. Delivered in partnership with INEOS Grenadiers, this unique studentship blends physics, computer science, and sport science to shape the future of race strategy at the highest level of the sport.
Open to: UK applicants
Funding providers: UKRI CASE Conversion and INEOS
Mode of study: Full-time, with time split between Swansea University and INEOS Grenadiers
Funding duration: 4 years
Professional cycling has undergone rapid tactical evolution in recent years, influenced by changes in course design, environmental conditions, peloton dynamics, team strategies, rider ability, and the increasingly sophisticated use of performance data. This PhD project aims to develop a deeper, evidence-based understanding of these factors to improve strategic planning and live race decision-making.
The successful candidate will work at the intersection of data science, performance modelling, and applied sport science, gaining hands-on experience within a WorldTour cycling team environment.
The main goal is to establish a comprehensive evidence base on professional road racing trends and identify the key tactical moments that influence race outcomes. This will involve:
- Historical race analysis:
Examine 3–5 years of data from Grand Tours, major one-day races, and select WorldTour stage races. Sources will include race video, rider power and speed data, and expert commentary. - Post-race analytical framework:
Develop processes and data-driven tools to deliver immediate tactical insights to Sport Directors. - Race prediction modelling:
Create a stage-race prediction model capable of informing real-time tactical decisions as races unfold.
Throughout the project, the candidate will play an active role in data collection, analysis, interpretation, and presentation within a professional performance environment.
Eligibility Criteria
Applicants must hold a 2:1 or above in one of the following disciplines:
- Mathematics
- Physics
- Computer Science
- Sport Science
A strong understanding of cycling performance science—particularly the metrics that drive race outcomes—is essential.
Highly desirable experience includes:
- Work or competitive experience in professional sport, ideally road cycling
- Data visualisation software (Power BI, Tableau, Google Data Studio)
- Programming skills (MATLAB, Python, R, C)
- Application of machine learning algorithms
English Language Requirements:
IELTS 6.5 overall (5.5+ in each component) or Swansea University–recognised equivalent.
This fully funded scholarship includes:
- Full tuition fees
- Annual UKRI stipend (£20,780 for 2025/26)
- Additional top-up stipend of at least £3,000 per year
- Research expenses of up to £1,000 annually
Closing date: 3 December 2025
Project start date: January 2026