38 condition-monitoring-machine-learning PhD positions at University of Nottingham in United-States
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from the globally renowned Power Electronics, Machines and Control (PEMC) Research Institute , University of Nottingham. The project will be supported by the state-of-the-art electric motor manufacturing
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offers an exciting opportunity to undertake cutting edge research in electrical machines within the globally renowned Power Electronics, Machines and Control (PEMC) Research Institute , University
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optimal operating conditions and followed by surface analysis techniques (e.g. Scanning electron microscope, X-ray diffraction for residual stress measurements, Electron Back-Scattered Diffraction and
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Digital-Twin Technology to Accelerate Development of Electric Propulsion Systems This exciting opportunity is based within the Power Electronics, Machine and Control Research Institute at Faculty
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Dr Sendy Phang. The student can gain experience and skills in a range of topics, such as Artificial Intelligence and Deep Learning, nanofabrication, computational modelling, metamaterial design, and
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Dr Sendy Phang. The student can gain experience and skills in a range of topics, such as Artificial Intelligence and Deep Learning, nanofabrication, computational modelling, metamaterial design, and
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computer literacy, good inter-personal communications skills. Desirable skills: A Master in Health Economics with experience in cost effective analyses. Funding notes The three year studentship covers UK
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working with complex data Enjoy learning beyond your current expertise with the support of our excellent interdisciplinary team Eligibility Start date: 1 October 2025 Open to applicants eligible for UK home
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suitable for a hard-working researcher with an interest in respiratory infections. Essential skills: A BSc degree or equivalent ideally in a health related field, excellent computer literacy, good inter
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key area of patient safety that can be improved with the use of computer vision approaches to system analysis. For many clinical procedures there can be multiple deviations in service delivery, which