2 PhD positions in Physics‑Informed Machine Learning for Traffic Modelling & Prediction

This PhD position involves developing next-generation traffic prediction methods by combining traffic flow theory with machine learning approaches like Physics-Informed Neural Networks. Candidates will work on hybrid traffic flow modeling, data assimilation, and network state estimation to improve the robustness and reliability of large-scale traffic networks. The role requires close collaboration with road authorities and industry partners to implement these methods in real-world operational environments.