Doctoral student in physics-informed neural networks for real-time control

Type de recrutement
KTH - Division of Decision and Control Systems
Fin de l'affichage

Project description: The Division of Decision and Control Systems is currently looking for up to two doctoral students with a very strong background and interest in physics-informed machine learning, mathematics, and learning for control. The successful candidates will join an interdisciplinary project on developing physics-informed machine learning models that would contribute to more efficient transmission of electric power. This project will be conducted in close cooperation with Hitachi Energy, the manufacturer of high-voltage components.

The Division of Decision and Control Systems conducts fundamental research in networked control systems, cyber-physical systems, system identification, and transport systems. Industrial projects involve partners such as Hitachi Energy, ABB, Ericsson, and Scania. A major part of the research is conducted within the framework of the Wallenberg AI, Autonomous Systems and Software Program (WASP). We have a large academic network and collaborate with researchers at Caltech, MIT, UC Berkeley, Stanford, among others.

Supervision: Kateryna Morozovska, Matthieu Barreau and Karl Henrik Johansson.