This is an opportunity to join a substantial research grouping to develop and implement new analytical methods for understanding the role of dynamic contact networks in the spread of infectious diseases. The successful applicant will join the Royal (Dick) School of Veterinary Studies and the Roslin Institute at the University of Edinburgh as a key part of a research team led by Prof. Rowland Kao. In this project, the postholder will exploit exceptionally well recorded data including densely recorded dynamic networks (livestock movement records) and where appropriate disease outbreak and pathogen sequence data in order to better quantify the relationships between dynamic network structure and the transmission of infectious diseases in order to inform prevention and control. It is anticipated that this work will both generate novel scientific outputs and have implications for government policy with impact on a variety of stakeholders.

The proposed work will both use existing techniques and require the development of innovative quantitative approaches, and so we are looking for an individual with a strong quantitative foundation (e.g. with Ph.D. level training in mathematics, statistics, physics, computing science, engineering or quantitative epidemiology or ecology) and evidence of working with "messy" data. Individuals with experience of network analysis and/or application of Bayesian inference approaches are especially encouraged to apply.

The post is open ended with an initial appointment to 31st December 2019, at which point it would be subject to review and renewal.

Informal enquiries may be directed to Prof. Rowland Kao (rowland.kao@ed.ac.uk)