19 machine-learning-"https:"-"https:"-"https:" PhD positions at University of Nottingham
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electric machines for future defence and aerospace propulsion systems. The research will explore innovative machine topologies and advanced multi-physics design methodologies to enable electric machines with
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filled The overarching aim of this project is to find synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application
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integrating power electronic converters and electrical machines we can use common structures and systems to greatly reduce, material usage and energy consumption. Through a multidisciplinary research approach
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integrating power electronic converters and electrical machines we can use common structures and systems to greatly reduce, material usage and energy consumption. Through a multidisciplinary research approach
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automotive and aerospace electrification. Applications for this PhD position are invited at the Power Electronics and Machines Centre, University of Nottingham. Based in a recently built £18M facility
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strain-rate/high temperature interface contact layer created during LFW of Titanium alloys and the links to key process variables and machine/tooling behaviour. This study will be undertaken using
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strain-rate/high temperature interface contact layer created during LFW of Titanium alloys and the links to key process variables and machine/tooling behaviour. This study will be undertaken using
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strain-rate/high temperature interface contact layer created during LFW of Titanium alloys and the links to key process variables and machine/tooling behaviour. This study will be undertaken using
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. Project Overview The project focuses on developing and applying advanced CFD models for aeroengine oil systems. There will also be opportunities to integrate machine learning techniques for building lower
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AI hardware beyond traditional computing architectures. Gain a unique combination of skills in mathematics, machine learning, and photonics. Be part of a multidisciplinary research team spanning