Senior Postdoctoral Research Scientist - Spatial Modelling Outbreak Response

University-of-Oxford; Oxford; Sur place; GBP 55 000 - 65 000; Plein temps

Résumé du poste

The Pandemic Sciences Institute at the University of Oxford is seeking a Senior Postdoctoral Research Scientist to join the Risk Modelling and Outbreak Response workstreams in the Kraemer Group. You will develop real-time spatiotemporal models of infectious disease outbreaks in resource-limited settings and contribute to forecasting, scenario modelling and reproducible computational pipelines.

You will work with Python, R, Julia and accompanying tools to integrate diverse data streams, build

Qualifications

• PhD/DPhil in a quantitative discipline (epidemiology, computer science, mathematics, statistics, or computational biology).
• Post-qualification research experience in a relevant field.
• Experience developing and deploying ML, mathematical, and statistical models for forecasting.
• Experience analysing complex spatial and spatiotemporal data; building reproducible pipelines.
• Proficiency in Python, R, Julia or similar languages.

Responsabilités

• Develop, implement and validate spatiotemporal models for infectious disease forecasting and scenario modelling.
• Integrate large-scale datasets across epidemiological, environmental, demographic, genomic, and behavioural modalities.
• Evaluate probabilistic forecasts and contribute to generalisable modelling tools and reproducible pipelines.
• Develop user‑facing dashboards and visualisations.
• Lead co‑design workshops and training with international partners to strengthen local capacity.

Description du poste

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.

The deadline for applications is 12:00 noon on Monday 23 November 2026.