Research Fellow: quantitative epidemiologist at Roslin Institute, Edinburgh

Closing date 1st December 2017

This is an exciting opportunity for a quantitative epidemiologist to join a vibrant veterinary epidemiology research group based in the Roslin Institute, University of Edinburgh. You will work with a large, multi-disciplinary team in the EPIC consortium, which contains epidemiologists, mathematical modellers, statisticians, social scientists and economists as well as experts in livestock diseases. The current position will work on livestock disease surveillance (topic 3) in a range of areas that include analysis to add value to existing data collections; developing statistical approaches to integrate and analyse surveillance datasets; developing tools to detect changes in population characteristics and developing risk based approaches to disease surveillance. There is considerable scope to develop new strands of work within the existing framework and the post-holder will be expected to participate in the development of other projects within EPIC, as well as future projects. The successful candidate will have formal epidemiological/statistical training to PhD level (or near completion) with, ideally, relevant post doc experience. They must work well within a team, have good communication skills and be comfortable working with and presenting to both scientists and government policy makers while being able to drive their own research within the remit of the project. Experience in implementing Bayesian graphical models, or related statistical methodologies, in R or other statistical platforms, would be highly desirable. Knowledge of the Scottish and European livestock industry would be an advantage.

Further Information

Applications and enquires are through The Roslin Institute.

All applicants are encouraged to apply online. The application process is quick and easy to follow, and you will receive email confirmation of safe receipt of your application. Applications should be received by the closing date of 01 December 2017.

Please quote reference number 041718 in all correspondence.


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