Doctorant F/H Doctorant(e) en intelligence artificielle scientifique et modélisation spatio-temporelle de la biodiversité

Develop scientific AI methods for understanding and predicting plant-community dynamics in space and time within the PEPR DynaBiod programme. Process-informed neural networks will combine data with ecological mechanisms, allowing inference from incomplete, heterogeneous and noisy observations. The project examines mathematical formulations, learning architectures and the recovery of ecological processes and parameters. A relevant master’s or engineering degree, scientific Python, machine learning or numerical modelling, and scientific English are required.

Appointment: 3 years; advertised start 2027-02-01. Rémunération brute mensuelle : 2300€.

Graduate degree or equivalent. Applicants may require authorization for access to a restricted research area (ZRR).