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- AALTO UNIVERSITY
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University explores synergies between nonlinear control theory and physics informed machine learning to provide formal guarantees on performance, safety, and robustness of robotic and learning-enabled systems
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and mathematical tools in quantum physics, quantum information theory, and related fields. It is a strong asset if you have already acquired expertise and demonstrated your ability to perform rigorous
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such as antenna arrays; and the modelling of advanced electromagnetic structures such as metasurfaces, which allow for unconventional control and manipulation of electromagnetic fields. Students who enjoy
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Modern cyber-physical systems (CPS), such as UAVs, next-generation fighter aircraft, and command-and-control (C2) platforms, integrate digital computation with physical processes to make mission
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Position Summary: Applications are invited for a PhD studentship, to be undertaken at Imperial College London (Control and Power Research Group, Department of Electrical and Electronic Engineering
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aforementioned tasks with the following actions: Develop the principles and theories for governing the scalability principles for building innovative robotics end-effectors that can access geometrically complex
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analytical frameworks grounded in Mean Field Game (MFG) theory and Multi-Agent Reinforcement Learning (MARL), which are tailored for eCPS. These frameworks will facilitate the creation of effective control