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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
predictive and explainable digital twins. The core challenge this PhD will tackle is how to help digital twins make sense of complex, messy maintenance data and turn it into clear, useful insights
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energy efficiency in electric aircraft, vehicles, and smart mobility systems. 3- AI-Assisted Radar, Sensing, and Navigation Electronics – Improve THz sensing, radar processing, and autonomous navigation
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electro-magnetic propagation and sensing with electro-optical (EO), infrared (IR) and radar systems. The main objectives of this project are: Investigation of the effects of high energy propagation in poor
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proposal, please feel free to contact Dr Alesia Ofori who will be able to help you develop this. This vacancy may be filled before the closing date so early application is strongly encouraged. For further
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unknown (not to worry – your case will be matched up with the appropriate expert for review) If you need any support in drafting the research proposal, please feel free to contact Paul Lighterness who will
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disruptive aircraft configurations involves combining advanced engineering practices, including computing power, sensing, AI/ML, and system-level engineering. Comprehensive verification and validation
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. This involves 'handcrafted' expert systems, which are good at reasoning about narrowly defined problems, but poor at handling uncertainty and have no ability to learn or abstract/generalise. In that sense