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Research Assistant in Sports Data Analytics for Anti-Doping

University of Kent - School of Sport and Exercise Sciences

Location: Canterbury
Salary: £27,924 to £32,344 per annum (grade 6)
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 9th September 2021
Closes: 27th September 2021
Job Ref: NATS-075-21

A postdoctoral research associate position is available in the School of Sport and Exercise Sciences at the University of Kent. We are looking for an enthusiastic and ambitious researcher who will work under the joint supervision of Professor James Hopker and Professor Jim Griffin (Department of Statistical Science, University College London), as well as working with leading international partners in anti-doping.

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. More information about the research can be found in the job description (see link below).

You will need to have sound knowledge of applied Bayesian methods and preferably with experience of modelling in biological or medical applications.

As Postdoctoral Research Associate you will:

  • Undertake research at an internationally competitive level
  • Contribute to the research project including the development and application of statistical methods
  • Design and execute the necessary experiments maintaining an up-to-date log of the research activity undertaken and of the obtained results
  • Carefully plan the research activity making sure the milestones of the project are achieved within the expected timeframe
  • Disseminate research results through peer-reviewed publications and conference presentations

To be successful in this role you will have/be: 

  • 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

Please see the links below to view the full job description and to apply for this post. If you require further information regarding the application process please contact the Human Resources team on quoting ref number: NATS-075-21


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