Summary:
The Institut Pasteur in Paris is seeking two postdoctoral researchers to engage in cutting-edge research within the Mathematical Modelling of Infectious Diseases Unit. The successful candidates will contribute to various projects focused on the application of statistical and mathematical methodologies to improve our understanding of epidemic dynamics and control.
Two Postdoctoral Positions in Epidemic Modelling, Paris, France
Designation:
Postdoctoral Researcher
| Field | Details |
|---|---|
| Research Area | Mathematical Modelling of Infectious Diseases |
| Location | 28 rue du Dr Roux, 75015 Paris, France |
| Applications Deadline | April 13, 2026 |
Eligibility/Qualification:
- PhD in: Infectious disease epidemiology, mathematics, statistics, physics, AI, computer science, population biology, or a similarly quantitative discipline.
- Skills Required:
- Experience with mathematical/statistical models and/or AI.
- Strong interest in infectious disease epidemiology.
- Proficiency in R programming; knowledge of C, C++, or Python is advantageous.
- Excellent communication skills.
Job Description:
The postdoctoral researchers will work on the following projects:
- Analyzing One Health data from a nationally representative serosurvey in Cambodia.
- Modelling influenza antibody landscapes globally.
- Using AI for epidemic preparedness.
- Forecasting plague epidemics in Madagascar.
- Comparing COVID-19, influenza, and RSV spread patterns in France.
- Studying how heterogeneous contacts in a population affect estimates of variant growth advantage.
Candidates will be supervised by Prof. Simon Cauchemez and collaborate with team members and partner institutions. Funding is available for one year, with potential for extension.
How to Apply:
Interested candidates should email Laurence Boutout (laurence.boutout@pasteur.fr) and Simon Cauchemez (simon.cauchemez@pasteur.fr) with:
- A CV
- A statement of interest
- Contact details for two referees (who will be contacted directly post-interview).
Last Date for Application:
April 13, 2026
Join us in advancing the field of infectious disease modelling and preparedness!
