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Position Summary: Applications are invited for a PhD studentship, to be undertaken at Imperial College London (Control and Power Research Group, Department of Electrical and Electronic Engineering
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expertise, and engagement with industrial partners driving innovation in aerospace materials. We welcome applications from motivated candidates with a background in materials science, mechanical engineering
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insights for streaming, broadcast, accessibility and media production. Candidate profile Applicants should have a background in machine learning, audio engineering, speech processing or a related discipline
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Brushless Doubly Fed Machines (BDFMs) are emerging as a promising technology for offshore wind turbine generators due to their fractional-sized power converters, elimination of rotor brushes and
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motivated students with a strong background in engineering or computer science. The ideal candidate will have: Strong programming and software skills. An awareness of machine learning theory and techniques
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geological field data. You will also design and run high-pressure shear-cell experiments on natural and analogue granular materials at Chengdu University of Technology, develop discrete-element simulations
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Computing & Digital Technology. Please complete the Doctoral Project Applicant Form , and include your CV and a covering letter to demonstrate how your skills and experience map to the aims and objectives
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universities (The University of Manchester , University of Glasgow and University of Oxford ). Robotics and Autonomous Systems (RAS) is an essential enabling technology for the Net Zero transition in the UK’s
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and Autonomous Systems (RAS) is an essential enabling technology for the Net Zero transition in the UK’s energy sector. However, significant technological and cultural barriers are limiting its
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expertise in hydrology, geomorphology, community co-development and social science? Based in the Department of Civil and Environmental Engineering, you will contribute to the research project ‘CONVERSE