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Position: Research Assistant in Sports Data Analytics for Anti-Doping
University of Kent
, Canterbury , Kent United Kingdom
Duties: The successful candidate will contribute to the development of Bayesian statistical models and inferential methods for athletic performance which can be used to develop better anti-doping procedures. The project will look at joint modelling of athlete performance and biomarkers and involve longitudinal random effects models, statistical detection of unusual sets of observations and Bayesian nonparametric methods. The project is funded by the World Anti-Doping Agency
Requirements: A PhD in (or nearing completion of study for one) or equivalent, in Statistics, Machine Learning, or a closely related discipline, especially with research interests in the application of Bayesian inference in biology or medicine, data science, or other related areas; In-depth knowledge and hands-on experience with Bayesian statistical approaches; Experience of handling, analysing and extracting information from large datasets; Excellent Matlab and/or R programming skills; Enthusiasm and motivation for research
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