We invite applications for a highly motivated and curiousity-driven postdoctoral scientist to join our interdisciplinary US-UK Collaborative project on viral dynamics in wildlife. The position will be based at the Royal Veterinary College within the Department of Pathobiology and Population Sciences (PPS), and the candidate will be integrated into a highly dynamic, international team with expertise in field epidemiology, wildlife ecology, genomic sequencing, machine learning, and capacity development.

The postholder’s key role will be to develop new methods to enable epidemiological inference from virus genomic (metaviromic) data generated from wildlife populations. Specific objectives include: 1) developing the underlying theory linking metaviromic data with models of epidemiological dynamics through computational simulations; 2) build a statistical framework to infer epidemiological dynamics from metaviromic data generated from longitudinal surveillance of wild rodent populations sampled across spatial and temporal scales; 3) use high-resolution host-virome data to determine how seasonal and anthropogenic environmental change influences viral incidence and epidemic growth rates.

We especially encourage applications from individuals with well-developed collaborative skills and strong interest in working at the intersection between ecology, epidemiology, and genomics. Knowledge and experience in statistical modelling and inference (particularly in dynamical systems and Bayesian statistics), a PhD in a relevant area (e.g. disease ecology, infectious disease dynamics, epidemiology, computational genomics or a related discipline), and programming (e.g. Python, C++, Java, R) are essential.

The successful candidate will join a small, growing group at the RVC with broad interests in virus ecology, evolution, and genomics. Furthermore, they will receive mentorship from diverse career stages and backgrounds and have opportunities to develop new and complementary skills and knowledge.

The post is open to international candidates and available for three years with a flexible start date from January to March 2025.