Description du sujet de thèse

Sujet : Development and Use of Stochastic Inference Methods in Biophysics

Description:This PhD project aims to develop advanced stochastic inference methods to extract equations of motion from noisy trajectories. The goal is to go beyond the white noise framework to address colored noise, which is ubiquitous in biological systems. The candidate will explore robust algorithms to reconstruct forces and noise structure from experimental data, with a particular focus on non-equilibrium dynamics. The developed methods will be applied to active matter systems (e.g. colloids, cells) and complex biological datasets. The project will build on analytical and numerical tools, in connection with the group's recent work. It is part of the ERC-funded SuperStoc project. Collaboration with experimental teams is possible.
Profile and skills required:Background in theoretical and statistical physics; strong programming skills; experience in experimental data analysis required.

Contexte de travail

Theoretical and numerical work in the PIV Department in CINaM.

Le poste se situe dans un secteur relevant de la protection du potentiel scientifique et technique (PPST), et nécessite donc, conformément à la réglementation, que votre arrivée soit autorisée par l'autorité compétente du MESR.

Contraintes et risques

None