Location: Life and Mind Building, South Parks Road, Oxford OX1 3EL
We are seeking a Senior Postdoctoral Research Scientist to join 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 and Dr Cathal Mills, you will help lead the development of a global, real-time, probabilistic forecasting observatory for climate-sensitive infectious diseases, including dengue, cholera, and malaria.
You will develop, implement, and validate spatiotemporal mathematical, statistical, and machine learning models for disease risk mapping, forecasting, and scenario modelling. You will integrate large-scale datasets across epidemiological, environmental, climatic, demographic, genomic, and behavioural modalities, evaluate probabilistic forecasts, maintain a public-facing forecasting dashboard, and work with international public health partners globally to support local model adoption through co-design workshops and training.
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 modelling climate-sensitive infectious diseases, developing and deploying forecasting and scenario models, and building reproducible analytical workflows in Python, R, Julia, and/or other relevant programming languages. Strong analytical, communication, organisational, and collaborative skills are essential.
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.
