Research Associate - Evolutionary Dynamics of Virus Resistance in Wild Animal Populations

Research Associate - Evolutionary Dynamics of Virus Resistance in Wild Animal Populations

University of Cambridge

Cambridge, United Kingdom

GBP 37,694 - GBP 46,049

Applications are invited for a Postdoctoral Research Associate position to work on a NERC-funded project investigating the evolutionary dynamics of virus resistance in wild animal populations. The post will be based in the Pathogen Dynamics Unit within the Department of Genetics at the University of Cambridge and be co-supervised by Professor Frank Jiggins and Professor Henrik Salje in collaboration with Prof Jon Slate at the University of Sheffield and Dr Joel Alves at the University of Oxford.

The Pathogen Dynamics Unit at the University of Cambridge consists of 15-20 researchers at different stages of their career using experimental, mathematical and computational research to help our understanding of how pathogens spread in populations. This post will work closely with the Slate group, which uses genomics approaches to study the evolution of quantitative traits.

The project will consist of the analysis of data from a population of wild rabbits in Australia that have been followed and sampled regularly for 25 years. During this period there have been regular outbreaks of Rabbit Haemorrhagic Disease Virus (RHDV), a highly contagious, often fatal virus. This project will use advanced quantitative genetics and epidemiological modelling to explore the evolution of resistance in the rabbit population and coevolution with the virus. This will include analysing several thousand host genomes from the 25-year period allowing us to investigate the evolution of host immunity from a quantitative genetic perspective. The project promises to provide fundamental insight into our understanding of disease ecology and evolution by exploring the interplay between host immunity and virus across long timeframes.

The applicant will have strong quantitative skills. The project will require the development of computationally intensive models and analysis of large genomic datasets, and therefore applicants should have experience in coding and a good understanding of probability, likelihoods and Bayesian analysis.

Key responsibilities:

• Develop models that integrate different data types (e.g., serology, epidemiological data, genomic data, demography) to understand the immune dynamics. Applying quantitative genetics approaches to a wild population. Analysis of genomic data.
• Write-up findings in manuscripts
• Work with study partners and researchers generating genomic data in the laboratory
• Present findings at conferences, external and internal meetings
• Be an active member of the Pathogen Dynamics Unit, including contributing to wider group discussions
• Supervision of students/Interns working in support of the research group