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design. Relevant research focus areas include, but are not limited to, hardware accelerators for machine learning (ML), Artificial Intelligence (AI), neuromorphic computing, and digital signal processing
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offered after successful completion of year 3. The bursary will be automatically rescinded if the student fails to successfully complete any academic year. Students on the extended programme are eligible
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detection of chemical and microbial contaminants in rivers. The studentship is funded by the Leverhulme Trust through the Connected Waters Leverhulme Doctoral Programme, which is supporting new research
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the wind/renewable energy training and research elements of the CDT programme. Funded by Statkraft and EPSRC, this 4 year this PhD studentship, at the University of Strathclyde is in the area of data
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of Sport, Exercise, and Nutrition Education – kimberley.edwards@nottingham.ac.uk This project is not funded, and we are seeking a student who can self-fund the PhD. Programme description: The overall theme
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You You are highly motivated, with a relevant undergraduate degree, or equivalent experience, in a relevant discipline. You have formal or equivalent experience in programme or project management, with
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, computer vision, and predictive modelling, alongside excellent IT, analytical, interpersonal and communication skills in spoken and written English. You must be able to collect, process and present data with
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understanding of a range of software packages, including the Microsoft Office suite of programs, database computer programs, Autodesk or other CAD software. Application Process To apply, please upload: • A
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their work at major international conferences. Applicants should have a 1st or high 2:1 honours degree (or international equivalent) in mathematics, physics, engineering, computer science or other related
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teaching for a diverse cohort of students on undergraduate and postgraduate Physical Geography and Environmental Science modules, including field work. We expect you to contribute to our Physical Geography