Research Assistant in Sports Data Analytics for Anti-Doping
  £27,924 to £32,344 per annum
  Canterbury, Kent
  contract,full-time

This Job Has Expired! This advert has now been deleted by the advertiser, the details below are for information only.


School of Sport and Exercise Sciences

Location: Canterbury
Salary: £27,924 to £32,344 per annum
Grade: Grade 6 Research Assistant
Post Type: Full Time
Contract Type: Fixed Term - 24 Months
Release Date: Monday 06 September 2021
Closing Date: 23.59 hours BST on Monday 27 September 2021 (unless otherwise stated)
Reference: 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



The School of Sport and Exercise Sciences is a leading department for the study of sport that is friendly, dynamic and innovative. Based on the University of Kent’s Canterbury Campus we are an ambitious academic department set up in 2001. The 2014 Research Excellence Framework was the School’s first research submission with the result of a GPA of 2.60 with over 50% of our work assessed as 3* or 4*. Our researchers publish extensively in leading journals and regularly secure external funding for their research. The Research Associate will also work closely with the Department of Statistical Science at the University College London. UCL have internationally-recognised research groups in applied and Bayesian statistics and were ranked 28th in the world in the QS ranking 2021.

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 NATSHR@kent.ac.uk quoting ref number: NATS-075-21


Advertiser: Direct Employer

Reference: NATS-075-21

Posted on: 2021-09-27 13:14:50

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Research Assistant in Sports Data Analytics for Anti-Doping
  £27,924 to £32,344 per annum
  Canterbury, Kent
  contract,full-time

This Job Has Expired! This advert has now been deleted by the advertiser, the details below are for information only.


School of Sport and Exercise Sciences

Location: Canterbury
Salary: £27,924 to £32,344 per annum
Grade: Grade 6 Research Assistant
Post Type: Full Time
Contract Type: Fixed Term - 24 Months
Release Date: Monday 06 September 2021
Closing Date: 23.59 hours BST on Monday 27 September 2021 (unless otherwise stated)
Reference: 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



The School of Sport and Exercise Sciences is a leading department for the study of sport that is friendly, dynamic and innovative. Based on the University of Kent’s Canterbury Campus we are an ambitious academic department set up in 2001. The 2014 Research Excellence Framework was the School’s first research submission with the result of a GPA of 2.60 with over 50% of our work assessed as 3* or 4*. Our researchers publish extensively in leading journals and regularly secure external funding for their research. The Research Associate will also work closely with the Department of Statistical Science at the University College London. UCL have internationally-recognised research groups in applied and Bayesian statistics and were ranked 28th in the world in the QS ranking 2021.

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 NATSHR@kent.ac.uk quoting ref number: NATS-075-21


Advertiser: Direct Employer

Reference: NATS-075-21

Posted on: 2021-09-27 13:14:50

I want to receive the latest job alerts for:

Education jobs in Canterbury, Kent

By creating a job alert, you agree to our Terms . You can change your consent settings at any time by unsubscribing or as detailed in our terms.

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