PhD in Control Theory for Learned Operators in Dynamical Systems

EURAXESS hosting organisation · Multiple European countries

Are you fascinated by the intersection of control theory and scientific machine learning? Join us in developing the mathematical foundations needed to make deep operators reliable, robust, and applicable for control of complex engineering systems. In this PhD project, you will investigate how operator-learning models can represent dynamical systems, how their stability and robustness can be characterized, and how controllers can be designed for them. Your work will combine rigorous theory, numerical methods, and applications in high-tech, medical, and energy systems. Information Modern engineering increasingly relies on data-driven models to describe complex dynamical systems. Scientific machine learning is now enabling a new class of models that learn operators mapping system inputs and i

Funding and what it does not cover

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