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by the ARC Trust and partners. The project will combine detailed three-dimensional habitat classification using cutting-edge technology with field-based tracking and tagging of individual frogs and
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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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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
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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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geometries and combine common materials in new ways to build bespoke, miniaturised antennas using magnetic nanoparticle structures. Your designs will make it possible to integrate digital technology platforms
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of full-time study. Eligibility: This studentship is available to home students only. The candidate should have a good 2.1 Bachelors, or Masters degree in Engineering, Computational or Physical Sciences