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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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equivalent in a related discipline. This project would suit motivated graduates from a wide range of STEM backgrounds—including environmental, civil, chemical or mechanical engineering, computer
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. The integration of AI into hardware not only enhances performance but also reduces energy consumption, addressing the growing demand for sustainable and efficient computing solutions. This PhD project delves
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We are looking for a highly motivated candidate to pursue a PhD programme titled "CFD-informed finite element analysis for thermal control in wire-arc directed energy deposition." This research
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, isolation, and prognostics. Machine Fault Simulator for Rotating Machinery Faults: A versatile platform that replicates common faults in rotating machinery, such as imbalance and misalignment, facilitating
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We are seeking a highly motivated candidate to undertake a PhD program titled "3D Temperature Field Reconstruction from Local Temperature Monitoring in Directed Energy Deposition." This exciting
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requirements A minimum of a 2:1 first degree in a relevant discipline/subject area (e.g. aerospace, automotive, mechanical, electrical, chemical, computing, and manufacturing) with a minimum 60% mark in
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electronics, embedded programming, signal processing, vibration measurement and analysis, maintenance engineering, and electro-mechanical engineering. Funding This is a self-funded PhD. Find out more about fees
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Applicants should have a first or second class UK honours degree or equivalent in in Design, Engineering, Computer Science/IT or a related subject. Experience in system design, and/or manufacturing is
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mechanism. The integrating should enable to guarantee certain properties of the learned functions, while keep leveraging the strength of the data-driven modelling. Most of, if not all, the traditional