10 machining-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"embl" Fellowship positions at University of Nottingham
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Are you completing / have completed a PhD in electrical machines or electromagnetics and looking for an ambitious next step in your research career? We are looking for a talented and highly
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About the Role A fantastic opportunity has arisen for a Senior Research Fellow to join the Power Electronics, Machines and Control (PEMC) Research Institute at the University of Nottingham and
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About the Role An exciting opportunity has arisen for an Application Engineer to join the Power Electronics, Machines and Control Institute (PEMC) at the University of Nottingham. This is a hands
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, clinical and sensor data processing, quantitative image analysis and machine learning. They will establish and maintain robust research databases and FAIR-compliant data management processes for large, multi
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. The focus of this specific role is the development of software tools that support the development of TOOLKIT: to develop and use machine learning and other computational tools to predict 3D printing outcomes
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In this role you will support the delivery of two exciting, EPSRC-funded research programmes at the University of Nottingham, working across AI, human-computer interaction, and creative technology
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About the Role An exciting opportunity has arisen for an Application Engineer to join the Power Electronics, Machines and Control Institute (PEMC) at the University of Nottingham. This is a hands
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of solid-state materials, with experience in density functional theory (DFT) and/or machine learning interatomic potentials. We welcome applicants with a broad range of research interests and experiences who
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relevant background in information extraction, entity resolution/entity linking, machine learning, uncertainty modelling, explainable AI, or a closely related area, with a PhD (or near completion) in
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Principal Investigator and a cell-culture specialist in a friendly, multidisciplinary group spanning optics, electrophysiology, microfabrication and machine learning, collaborating with partners