Description: This project bridges physics-informed architectures (PINNS, PIANNS) with Meta-RL to create mathematically grounded, adaptive agents Possible collaborator contributions: Algorithm design Implementation, training pipelines and rigorous experiments Theoretical insights (control theory, approximation, stability) Requirements (one or more) PhD in CS/math/physics or related field OR 2+ relevant peer-reviewed publications as the first author OR 2+ years industry experience as AI engineer/researcher Good PyTorch or JAX skills expected Commitment ≥8 h/week and Bi-weekly Zoom calls