Laboratory of Sports Studies Opens Position for Russian Postdoctoral Fellow

The Laboratory of Sports Studies has an open position for a Research Fellow (postdoctoral fellow) to work on research related to 'Humans vs AI in Sport'.

Artificial intelligence technologies are actively making their way into sport (e.g., Zhou et al., 2025). Key areas where they are already being applied include optimising training processes to minimise injury risk, improving athletes' performance through better strategic choices, talent identification, social media analysis for marketing purposes, and other applications. The Laboratory of Sports Studies is also carrying out projects related to AI in sport, in particular studying the predictive capabilities of large language models.

The postdoctoral fellow will be offered a research direction focused on studying the behaviour of LLMs in settings involving strategic interaction between athletes and teams. In economics, a growing strand of research replicates experiments previously conducted with human participants using LLMs instead. The goal of such experiments is to understand how the behaviour of large language models differs from that of humans under the same conditions.

The goal of this project will likewise be to compare the behaviour of LLMs and representatives of the sports industry in identical situations of strategic interaction in sporting contexts.

References:

Zhou, D., Keogh, J. W., Ma, Y., Tong, R. K., Khan, A. R., & Jennings, N. R. (2025). Artificial intelligence in sport: A narrative review of applications, challenges and future trends. Journal of Sports Sciences (forthcoming).

You can apply for the position via the following link.

What we expect from successful candidates for the Russian postdoctoral position:

• Russian citizenship, or foreign citizenship provided the candidate obtained their academic degree in Russia;
• An academic degree (Candidate of Sciences degree, a successfully defended Candidate of Sciences dissertation, or a PhD degree);
• We expect candidates to have experience working with various large language models, a command of mathematics at the level of standard university courses, and skills in econometric analysis and/or machine learning methods. Familiarity with the sports industry will be an advantage (especially if the candidate has been an athlete themselves), but this is not a mandatory requirement. In any case, enthusiasm and a genuine drive to work hard outweigh everything else.