Salary £37,904 – £45,547
Duration 12 months in the first instance
Location St Mary’s Campus, Paddington
Closing date 9 December 2018
Reference MED00874
We seek a mathematical modeller to develop innovative models and inference methodology to improve our understanding of the spatial spread of pandemic and seasonal influenza, and to use these models to evaluate the impact of control strategies (in particular vaccination) in the short and long-term in order to inform public health policies.
With the emergence of a new pandemic strain in 2009, the constant threat from cross-species emergence and the recent decision by the UK Joint Committee on Vaccination and Immunisation to extend seasonal vaccination to school-aged children, there are few public health issues currently of greater importance than influenza transmission in terms of impact on the health of society. This project will contribute to the innovative research required to identify and rigorously evaluate optimal responses to the threat from circulating respiratory viruses.
Candidates will require a PhD in one of the following areas: infectious disease epidemiology, population biology, mathematics, statistics, theoretical physics, computer science or a similarly quantitative discipline. You will also require a first degree in a scientific or mathematical discipline. You will also have postgraduate experience of developing dynamical models of biological or physical systems and of parameter estimation with such models and the ability to present information effectively at meetings, and give positive input to discussions at meetings.
The full job description is online. Go to https://www.imperial.ac.uk/jobs/ and search for “MED00874”. Applications should be submitted via the Imperial College online system.
Interested candidates should contact Dr Marc Baguelin (marc.baguelin@phe.gov.uk) or Professor Neil Ferguson (neil.ferguson@imperial.ac.uk).
Interviews are expected to be held approximately 2 weeks after the closing date. Applicants who are invited for interview will be asked to give a short presentation explaining how they meet the selection criteria.