Senior Postdoctoral Research Scientist - Spatial Modelling Outbreak Response

University Of Oxford; Oxford; Sur place; GBP 42 000 - 54 000; Plein temps

Résumé du poste

University of Oxford seeks a Senior Postdoctoral Research Scientist to advance real-time spatiotemporal models for infectious disease outbreaks. You will develop forecasting models, validate them on large integrated datasets, and build reproducible computational pipelines in Python, R, and Julia.

You will also contribute to dashboards and training with international partners. The role is a fixed-term, full-time appointment until 31 January 2028, funded by the Medical Research Foundation, with

Qualifications

• PhD/DPhil in a quantitative discipline with post-qualification research experience.
• Experience developing and deploying machine learning, mathematical, and statistical models for forecasting.
• Ability to analyse complex spatial and spatiotemporal data and build reproducible pipelines.

Responsabilités

• Develop and implement real-time spatiotemporal models of infectious disease outbreaks.
• Evaluate probabilistic forecasts and contribute to reusable modelling tools and pipelines.
• Develop dashboards and visualisations and train partners through co-design workshops.

Connaissances

Spatiotemporal modelling

Epidemiology

Data analysis

Machine learning

Formation

PhD/DPhil in a quantitative discipline

Outils

Python

R

Julia

Description du poste

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.