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Health and Life Science Faculty

This NERC-funded post is available full time from 1st January 2026 to 31st December 2030

The post
The Faculty wishes to recruit a Postdoctoral Research Fellow to participate in a 5-year, large-grant project on the epidemiology of bovine tuberculosis in wild badgers, using state-of-the-art Bayesian modelling approaches to study the drivers of infectiousness and transmission of infection in an intensively monitored wildlife disease system, with real-world applications for UK agriculture and conservation science. This NERC-funded post is available from 1st January 2026 to 31st December 2031. The successful applicant will use state of the art inference algorithms to design, use and share the findings of epidemiological models that integrate across large and diverse datasets including capture-mark-recapture for demography and social network structure; genome re-sequencing for pedigree information and genomic prediction; diagnostic testing for infection status and prevalence of bTB. The Research Fellow will join a team of five postdoctoral researchers, research faculty from Universities of Exeter, Sheffield and Edinburgh, and project partners from the Animal and Plant Health Agency, DEFRA and the Office for Environmental Protection.

The post will include the design, development and translation of Bayesian epidemiological compartmental models, using large and long-term datasets to support their inferences. The Fellow will work with team members to develop models to quantify evidence regarding the effects of social, demographic, age-dependent, kin-related and genetic drivers of susceptibility to infection and of onward transmission of infection, among host individuals. The Fellow will be responsible for coordination of collaborative epidemiological research using these models, and for leading primary research outputs, presenting findings at conferences and workshops, and engaging in impact-related activities with stakeholders.

About you
The successful applicant will be able to develop research objectives, projects and proposals; engage in collaborative research with real-world impact; and make presentations at conferences, workshops and other events.

Applicants will possess a relevant PhD or equivalent qualification/experience in a related field of study. The successful applicant will have expertise in statistical modelling, epidemiology or machine learning and possess sufficient specialist knowledge in the discipline to develop research methodologies. The successful applicant will be able to work collaboratively, supervise the work of others and act as team leader as required.. Applicants will have excellent written and verbal communication skills, experience with developing and implementing Bayesian statistical models, and be proficient in computer programming in e.g. R or Python, and C/C++.


Please ensure you read the Job Description and Person Specification for full details of this role.

What we can offer you
• Freedom (and the support) to pursue your intellectual interests and to work creatively across disciplines to produce internationally exciting research;
• Support teams that understand the University wide research and teaching goals and partner with our academics accordingly
• An Innovation, Impact and Business directorate that works closely with our academics providing specialist support for external engagement and development
• Our Exeter Academic initiative supporting high performing academics to achieve their potential and develop their career
• A multitude of staff benefits including sector leading benefits around maternity, adoption and shared parental leave (up to 26 weeks full pay), Paternity leave (up to 6 weeks full pay), and a Fertility Treatment Policy
• Beautiful campuses set in the heart of stunning Devon and Cornwall. The project will be lead from our Cornwall campus.

The University of Exeter

The University of Exeter is an equal opportunity employer. We are officially recognised as a Disability Confident employer and an Athena Swan accredited institution. Whilst all applicants will be judged on merit alone, we particularly welcome applications from groups currently underrepresented in the workforce.

For further information please contact Professor Trevelyan McKinley, e-mail T.McKinley@exeter.ac.uk or Professor Dave Hodgson, email D.J.Hodgson@exeter.ac.uk.