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trade-offs between efficiency, cost, and emission control. To fully realise ammonia’s potential as a clean energy carrier, a fundamental rethinking of the combustion process is needed. This PhD project
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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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Supervisors Primary Supervisor - Dr Calum Williams Secondary Supervisors - Dr. Maciej Dabrowski , Prof Simon Horsley This PhD studentship will develop 3D-printed optical metamaterials to control
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- skills – experience: analytical skills, ability to demonstrate good knowledge in system modelling – simulation, (classical or modern) control theories or control applications with evidence Desirable
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research environment. Opportunity to shape next generation control theory within a world leading research group and to collaborate with major energy sector partners. Access to Imperial’s high‑performance
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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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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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in physics is not possible without acknowledging the crucial role of observations and context in the foundations of quantum theory. If you are interested in deepening our conceptual understanding
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not possible without acknowledging the crucial role of observations and context in the foundations of quantum theory. If you are interested in deepening our conceptual understanding of the intersection
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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