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stages have not seen widespread use due to the low thrust of electric propulsion (EP), leading to slow transfer times. Magdrive are developing the high-thrust SuperMagdrive propulsion system targeting 1N
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supporting the Net Zero 2050 target. This PhD project will develop an AI-enabled framework that optimizes wind turbine control and predictive maintenance. Using Deep Reinforcement Learning (DRL), the system
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This self-funded PhD research project aims to advance the emerging research topics on physics-informed machine learning techniques with the targeted application on predictive maintenance (PdM
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leadership capabilities. Advances in aero-engine technologies are expected to play a key role in reducing aviation emissions as part of the NetZero targets. This new experimental based research will focus
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refuelling infrastructure for aviation applications. It will directly contribute to the UK’s Jet Zero and Net Zero targets by reducing engineering conservatisms and enabling safer, more efficient use of
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capabilities. Advances in aero-engine technologies are expected to play a key role in reducing aviation emissions as part of the NetZero targets. Within that context, advances in experimental and computational
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. This project will deliver practical solutions enabling safe and efficient hydrogen storage and transportation in aerospace components, directly contributing to the UK’s Jet Zero and Net Zero targets. It will
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are expected to include: •Robust and “functionally explainable” machine-aided decision support for Safety and Mission Critical objectives e.g. fault detection/tracing, evasive manoeuvring, target selection etc