Stage

M2 Internship: Physics Informed Neural Networks for parameter estimation in Stochastic Differential Equations

L'offre est déjà pourvue (20/02/2026)

Context

Stochastic Differential Equations (SDEs) are popular models in many fields including spatial ecology, climate science, biology. Diffusion SDEs with additive noise are commonly found. When proposing such a model for observed trajectories at discrete times, the next step consists in estimating the SDE parameters from those observed data. This is a critical task from which one can gain understanding on the underlying process mechanics.