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by UK utility SP Energy Networks, and is used to automate the selection, siting and sizing of network operator-owned active PEDs. An initial design for the Tool has been developed through 2025, and
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adapting their energy use, control strategies, and collective behaviours to enhance sustainability. The research aims to design AI-driven control and energy management frameworks that enable self-organising
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engines, alternative fuels, combustion optimisation, and powertrain control. As the automotive industry transitions towards electrification, integrating novel fuels—such as hydrogen, ammonia, e-fuels, and
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focus on the medical image processing aspect of the Birth4Cast simulator by researching and developing automated image segmentation procedures to extract the pelvic floor muscle complex and the fetal head
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. The project focuses on power-aware computing, thermal optimization, and sustainable electronic design, targeting critical applications in aerospace, healthcare, and industrial automation. Hosted by the renowned
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to measurable safety metrics and relevant regulatory norms. Automate this pipeline to support scalable, simulation-based compliance checking. The outcomes will include a formal DCD framework, a prototype
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-matter interactions control and optimisation. The PhD will advance our comprehension of the mechanisms that lead to defect formation in DED-LB, and improve process control measures to either prevent
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focuses on AI-driven fault diagnosis, predictive analytics, and embedded self-healing mechanisms, with applications in aerospace, robotics, smart energy, and industrial automation. Based
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-free method for nitrogen fixation into liquid nitrogen fertilizer for controlled on farm application. This project combines an atmospheric pressure plasma process with a catalyst, aiming to provide a
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ecosystem, including a mobile app to control the eLFA and a cloud-based AI analytics platform. This role will also get hands-on with validation, conducting wet lab experiments with real food samples to refine