Hard and soft constraints in Scientific machine learning (SciML)

We are recruiting a fully funded PhD student at FEMTO-ST / SUPMICROTECH in Besançon, France, on the topic: Hard and Soft Constraints in Scientific Machine Learning (SciML). The project will explore how physical constraints can be integrated into machine learning models, combining physics-informed AI, dynamical systems, control theory, and applications in robotics and neuroscience. We are looking for candidates with a strong background in machine learning, applied mathematics, control, or scientific computing, along with solid Python programming skills. 📅 Start: September 2026 🗓️ Deadline: June 15, 2026 For more details, please check the attached PhD offer and feel free to share it with interested candidates.