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View All Vacancies Chemistry Location: UK Other Closing Date: Sunday 12 May 2024 Reference: SCI266 Uncertainty quantification for machine learning models of chemical reactivity In this PhD
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electrical machines, drives and materials are required.? The PEMC research group has grown exponentially and now has over 200 members, 24 academics and circa 130 PhD students, researchers, and engineers
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the Electrical Revolution Industrialisation Centre as part of the Power Electronics, Machines and Drives Research Group (PEMC) at the University of Nottingham and become a core member of a team working on
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takes input from a machine-learning platform (Python-based) to produce new compositions. A cobot delivers the material to the furnace or a plasma spray to produce new coatings. The proposed research is
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related to testing electrical machines, drives and materials are required. The PEMC research group has grown exponentially and now has over 200 members, 24 academics and circa 130 PhD students, researchers
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quantitative methods, data skills and machine learning methods for effectively handling micro-level panel data, providing valuable skills for future careers. A Masters degree is not a prerequisite. Undergraduate
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experience in electrical machine design is required.? Candidates should hold or be shortly due to obtain a PhD, or equivalent in Electrical Engineering related to work on Power Electronic Converters or a very
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. This project focuses on building confidence in ASL when coupled with our advanced machine learning tools for clinical application in dementia. Supervisor: Prof Michael Chappell Eligibility: https
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will be to shortcut the current search process in classify crystallographic orientation. This will be built upon where machine learning algorithms will be developed to extract material elasticity
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the Electrical Revolution Industrialisation Centre as part of the Power Electronics, Machines and Drives Research Group (PEMC) at the University of Nottingham. You will be a core member of a team working on