Senior Postdoctoral Research Scientist – Climate Sensitive Infectious Diseases

University of Oxford; Oxford; On-site; GBP 45,000 - 60,000; Full time

Job summary

The University of Oxford seeks a Senior Postdoctoral Research Scientist to lead development of a global, real-time probabilistic forecasting observatory for climate-sensitive infectious diseases, including dengue, cholera, and malaria. You will build, validate, and deploy spatiotemporal models and work with international partners to translate findings into practice.

You will hold a PhD with post-qualification experience in a quantitative field and have strong Python/R/Julia skills, with a track

Qualifications

• Hold a PhD/DPhil in a quantitative discipline such as epidemiology, computer science, mathematics, statistics or computational biology.
• Demonstrable experience modelling climate-sensitive infectious diseases and deploying forecasting and scenario models.
• Experience building reproducible analytical workflows in Python, R, Julia or similar languages.

Responsibilities

• Develop, implement and validate spatiotemporal models for disease risk mapping and forecasting.
• Integrate large datasets across epidemiological, environmental, climatic, demographic, genomic and behavioral modalities.
• Maintain a public-facing forecasting dashboard and collaborate with international public health partners.
• Contribute to co-design workshops and training to support local model adoption.

Skills

Spatiotemporal modelling

Forecasting

Python

R

Julia

Data analysis

Communication

Education

PhD / DPhil in a quantitative discipline

Tools

Python

R

Julia

Job description

Senior Postdoctoral Research Scientist – Climate Sensitive Infectious Diseases

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.

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