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Field
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primary regenerative braking. EMBs are highly sensitive to EV harsh operating conditions. This project addresses this challenge by developing AI-based EMB clamping force estimators and robust control
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Engineering, Control Engineering, Mechatronics, Robotics, or a related discipline with a strong focus on dynamic systems. Strong background in state-space modelling, estimation theory, and control systems. Good
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intrinsic stability or robustness properties. You will also investigate how physical insight, prior system knowledge, and stabilizing baseline controllers can be combined with learning to improve performance
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activation, reliability, robustness and the fact that they are maintenance-free. Despite these many advantages, the exact mechanisms that control performance in industrially utilised thermal batteries has
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embedded into cyber‑physical systems (CPS) such as autonomous vehicles, smart grids, industrial control systems, robotics, healthcare devices, and intelligent transport infrastructure. While significant
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for Applied Power Electronic Systems. You will join an interdisciplinary team working across electrolysers, Power-to-X systems, power electronics, control, digital twins, and energy-system optimization, in
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sites, highly engineered geological repositories or in the marine environment. However, redox controls on porewater chemistry in these environments is poorly understood and requires robust datasets
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₂ reduction, aimed at producing hydrogen as an energy carrier and value-added chemicals such as CO and formic acid (HCOOH), requires efficient, selective, and robust catalysts. These catalysts must operate
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information about the dielectric properties of the surface and can therefore be used to infer changes in soil moisture. A major focus of the PhD will be to develop, test and improve robust GNSS-IR processing
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Engineers usually want predictability. This project embraces chaos! – Excited about control theory? Then join us to build the math of chaotic sampling for greener and more secure control systems