Duties: The main aim of the project the post-holder will join is to develop, improve and apply models for improving situational awareness and informing data collection in outbreaks via data analysis and forecasting. Including systematic assessment of the predictive ability of any forecasts made, and whether the inclusion of individual, spatial, behavioural or genetic data can improve them. There is considerable freedom for work within the aims of the project and scope for the development and use of state-of-the-art methodology and computation with direct impact on public health
Requirements: The successful applicant will have a postgraduate degree, ideally a doctoral degree in a quantitative discipline such as epidemiology, mathematics, physics, statistics, bioinformatics or computational biology, or similar research experience. Candidates should have proficient knowledge of a programming language for mathematical or statistical modelling, including some experience with R, and be committed to open research and/or software development. Experience in outbreak analysis or model-based forecasting is an advantage

Duties: The successful candidate will develop epidemiological models to understand the risks and benefits of introducing maternal respiratory syncytial virus (RSV) vaccination in low- and middle-income countries. A new maternal RSV vaccine has been developed that has the potential to save the lives of infants from dying from RSV, but which may be potentially linked to a higher risk of preterm birth. This work will inform guidance from WHO about whether to use the vaccine
Requirements: A postgraduate degree, ideally a doctoral degree, in a relevant topic; Relevant experience in mathematical modelling, health economics, epidemiology, statistics or another relevant discipline with a strong quantitative component; Experience in a relevant computer programming language, preferably R