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PhD Studentship: Building a profile of Formula racing drivers at different stages of development

Manchester Metropolitan University

Qualification Type: PhD
Location: Manchester
Funding for: UK Students, EU Students, International Students
Funding amount: £19,237 per annum
Hours: Full Time
Placed On: 19th September 2024
Closes: 14th October 2024
Reference: 115060-9

This project provides an annual stipend of £19,237. 

Project advert

There is a shortage of high-quality data relating to the key determinants of driving performance, and the anthropometric, physical, psychological, and cognitive characteristics of elite Formula 1 racing drivers, with even less on drivers across different stages of development (e.g., karting to Formula 2). Whilst an understanding of the key determinants of performance, and characteristics of successful performance, is vital to optimise driver training and development, this information is currently unavailable. As such, team managers, drivers, and conditioning coaches are lacking the required information to implement effective training and monitoring programmes across stages of driver development.

This PhD programme will investigate the anthropometric, physical, physiological, psychological, and cognitive characteristics of Formula racing drivers across stages of development (i.e., karting, F4, F3, F2, F1), and identify the key determinants performance. The findings of this work will provide information to inform the selection, training, and development of male and female Formula racing car drivers, raising performance standards across the sport. Work will utilise the world class facilities in the Institute of Sport within Manchester Met.

Project aims and objectives

This project aims to investigate the key anthropometric, physical, psychological, and cognitive characteristics that differentiate performance standards across different stages of development in Formula series racing drivers, providing:

  • A robust and effective profiling battery; informing future practice.
  • A high-quality dataset; exceeding previous published methodological standards.
  • A novel dataset; addressing gaps in current knowledge and understanding.
  • Guidance for team managers, drivers, and conditioning coaches; on the selection, training, and development of female and male racing drivers.
  • Support to More Than Equal’s mission to find the first female Formula 1 world champion.

Specific requirements of the candidate

We are looking for a PhD researcher to investigate the anthropometric, physical, physiological, psychological, and cognitive determinants of Formula driving across different stages of development. The studies will have an applied and basic-science focus, and there is scope for the PhD researcher to input into the techniques and measures included in this programme of work. Applicants should have:

  • Knowledge and experience of standard research techniques and methods within sport and exercise science, and the ability to develop skills further in this area, particularly in the physical profiling and development of athletes;
  • The ability to collate, interpret, and analyse data;
  • A keen and active interest in the physical determinants, and development of elite sport performance.

How to apply

Interested applicants should contact Dr Laurence Birdsey for an informal discussion.

To apply you will need to complete the online application form for a full-time PhD in Elite Performance (or download the PGR application form).

You should also complete the (PGR thesis proposal and a Narrative CV) form addressing the project’s aims and objectives, demonstrating how the skills you have maps to the area of research and why you see this area as being of importance and interest. 

If applying online, you will need to upload your statement in the supporting documents section, or email the application form and statement to PGRAdmissions@mmu.ac.uk.

Closing date: 14 October 2024. Expected start date: January 2025 for Home students. This opportunity is not available for International students. 

Please quote the reference: SciEng-2024-Profile-Formula-Racing

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