Postdoctoral Researcher in Stochastic Modelling for Population Genetics
Develop novel stochastic models for transposable element dynamics in host genomes using branching processes and SLiM simulations.
Best for:Best for postdoctoral researchers with expertise in stochastic processes, branching models, and population genetics, seeking to contribute to interdisciplinary research at the intersection of mathematics and biology.
Overview
This postdoctoral position at INRAE’s BioSP research unit in Avignon focuses on advancing stochastic modelling for population genetics. The project, funded under the ANR JCJC programme, aims to create inference tools for epidemiology by studying the dynamics of transposable elements within host genomes. The successful candidate will work on neutral and extended models of transposition dynamics, integrating Wright-Fisher models and branching processes, and compare results with empirical data on *Blumeria hordei*. Collaboration with Prof. Aurélien Tellier’s group at TU Munich is integral to this research.
What you'll do
- Study the quasi-stationary dynamics of neutral models for transposition dynamics using Wright-Fisher and branching process frameworks.
- Extend existing modelling frameworks to incorporate effects of transposons on host cell reproduction dynamics and analyze these models analytically or via SLiM simulations.
- Compare model predictions with empirical data on the powdery mildew *Blumeria hordei* in collaboration with Prof. Aurélien Tellier’s group at TU Munich.
- Develop new inference tools for epidemiology based on probabilistic models of structured biological assemblages.
- Publish findings in peer-reviewed journals and present results at relevant scientific conferences.
Requirements
Degree required: PhD in applied mathematics, statistics, computational biology, or a related quantitative field
Language: English; proficiency sufficient for academic research and collaboration
Instruction: French (work environment) and English (research collaboration)
- Expertise in branching processes and stochastic processes
- Experience with stochastic models for population genetics
- Familiarity with SLiM simulation framework
- Strong background in mathematical modelling
- Proficiency in analytical and computational techniques
- PhD degree in a relevant field
- No specific nationality or residency restrictions mentioned
- No age or prior experience caps mentioned
Funding & terms
How to apply
Deadline: 2026-10-20
Applicants must submit a CV, a cover letter, and a 2-page research work presentation to apolline.louvet@inrae.fr. Ensure all documents are concise and highlight relevant research experience.
- CV
- Cover letter
- Presentation of research works (max 2 pages)
Contact
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