Summary of the role
The College wishes to recruit a Postdoctoral Research Fellow in Statistical Infectious Disease Modelling to participate in an exciting project developing novel statistical methodology for inference and prediction in complex infectious disease systems, with a focus on infectious diseases in wildlife (notably bovine tuberculosis in badgers). This NERC-funded post for two years is available immediately or by negotiation. The successful applicant will extend and develop novel simulation-based inference methods for fitting complex infectious disease models to partially observed data. The proposal addresses the pressing need for efficient, flexible and powerful approaches to understand transmission dynamics of wildlife infectious diseases, that deal with important real-world complexities such as incomplete surveillance and diagnoses, longitudinal changes in host demography and spatio-temporal patterns of spread. A key focus is on the development of robust methods for fitting and comparing between competing model structures. This novel research will provide crucial information on the mechanistic drivers of disease transmission that is necessary to inform evidence-based management policies.
About you
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. 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++.
Find out more and apply online.
