Interdisciplinary PhD in evolutionary biology and statistical mechanics M/F

Job Description

Thesis Subject

This PhD project lies at the interface between probability theory, statistical physics, and evolutionary biology. It aims to understand how finite populations change regime under the joint effect of mutation and selection landscapes, using Moran models and modern tools from large deviation theory.

Moran models provide a minimal yet powerful framework to study fixation, coexistence, genetic diversity, and finite-size effects. In statistical physics, related questions arise in the study of rare events, characterized by atypical fluctuations or abrupt transitions. The project is based on a central idea: population-dynamics algorithms used to simulate large deviations have a structure close to evolutionary models with mutation and selection. This connection will be used in both directions.

The PhD candidate will first study simple models where the nonlinear dynamics of a population can be compared explicitly with a linear spectral problem from large deviation theory. The analysis will focus on eigenvalues and eigenvectors, rate functions, and associated Doob transforms, together with numerical simulations. A central question will be to identify when varying a parameter — for instance the mutation/selection ratio — induces an abrupt change in the trait distribution, analogous to a phase transition.

The project will then be extended to richer settings: multiple traits, community graphs, heterogeneities, and possibly populations whose total size is no longer conserved. The goal is to identify general criteria linking mutation landscapes, selection landscapes, observed diversity, and genealogical properties.

The interdisciplinary nature of the project is central: probability theory provides the rigorous framework, statistical physics brings large-deviation tools for rare fluctuations and phase transitions, and evolutionary biology supplies the questions and phenomena to explain. The thesis is expected to produce theoretical results on Moran models, new algorithms for large deviations, and insights into the emergence of diversity in evolving populations.

Expected skills: analytical methods in nonequilibrium statistical physics, Markov chains, diffusions, eco-evolutionary models, and quantitative approaches to living systems.

Your Work Environment

Co-supervision with Charline Smadi (Institut Fourier and INRAE, Université Grenoble Alpes).

Interdisciplinary PhD project at the interface of theoretical physics, mathematics (probability theory), and evolutionary modelling.

CNRS MITI 80Prime funding (PI: Charline Smadi).

Collaborations: Sara Dal Cengio (MIT / CNRS), Sylvain Billiard (Univ. Lille), Julien Tailleur (MIT).

LIPhy is an interdisciplinary laboratory, mainly experimental, with a theoretical component including statistical physics. The host team, PSM, focuses on modelling and analytical approaches in nonequilibrium physics. The Institut Fourier, as co-supervising laboratory, is a laboratory of mathematics, whose probability group has strong expertise in eco-evolutionary models.

Constraints and risks

None

Compensation and benefits

Compensation

2300 € gross monthly

Annual leave and RTT

44 jours

Remote Working practice and compensation

Pratique et indemnisation du TT

Transport

Prise en charge à 75% du coût et forfait mobilité durable jusqu’à 300€

About the offer

About the CNRS

The CNRS is a major player in fundamental research on a global scale. The CNRS is the only French organization active in all scientific fields. Its unique position as a multi-specialist allows it to bring together different disciplines to address the most important challenges of the contemporary world, in connection with the actors of change.

CNRS

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