Location: Life and Mind Building, South Parks Road, Oxford OX1 3EL
We are seeking a Senior Postdoctoral Research Scientist to join the Risk Modelling and Outbreak Response workstreams of the Kraemer Group in the Data Analytics and Epidemiology (DAE) group at the Pandemic Sciences Institute (PSI), University of Oxford. Working with Professor Moritz Kraemer, Dr Cathal Mills, and Dr Ciara Judge, you will focus on developing and implementing real-time, spatiotemporal models of infectious disease outbreaks in resource-limited settings.
You will develop, implement, and validate spatiotemporal models for infectious disease forecasting and scenario modelling, and integrate large-scale datasets across epidemiological, environmental, demographic, genomic, and behavioural modalities. You will evaluate probabilistic forecasts, contribute to generalisable modelling tools, software, and reproducible computational pipelines, develop user-facing dashboards and visualisations, and lead co-design workshops and training with international partners to strengthen local capacity and inform outbreak response.
You will hold a PhD/DPhil with post-qualification research experience in a relevant quantitative discipline (such as epidemiology, computer science, mathematics, statistics, or computational biology). You will have demonstrable experience developing and deploying machine learning, mathematical, and statistical models for infectious disease forecasting and scenario modelling, analysing complex spatial and spatiotemporal data, and building reproducible computational pipelines in Python, R, Julia, and/or other relevant programming languages.
The University of Oxford is committed to equality and valuing diversity. All applicants will be judged on merit, according to the selection criteria.
This post is full-time on a fixed-term contract until 31st January 2028, funded by the Medical Research Foundation (MRF), and available immediately.
Applications for this vacancy should be made online via our e-recruitment system, and you will be required to upload a supporting statement and CV as part of your online application (via the 'Apply' button above). Your supporting statement must explain how you meet each of the selection criteria for the post using examples of your skills and experience. Please restrict your documentation to your CV and supporting statement only. Any other documents will be requested at a later date. The deadline for applications is 12:00 noon on Monday 23 November 2026.
