62 phd-studenship-in-computer-vision-and-machine-learning Fellowship positions at University of Nottingham
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The EPSRC Postdoctoral Pathway Prize (formerly Doctoral Prize) provides opportunities for the most outstanding EPSRC-funded PhD students to receive up to 12 months (FTE) of additional support
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to work with modern massively-parallel simulation codes. Candidates must have (or be close to completion of) a PhD in astrophysics or a related subject, and a BSc/MPhys (or equivalent) degree in physics
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and closely with other members of the project team. About you We are looking for a motivated, highly qualified individual with a PhD in criminology, law, social sciences or a cognate discipline, who
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and the manager of your substantive post, if you are already undertaking a secondment role. The Leverhulme Trust’s funding regulations mean that individuals will have needed to have submitted their PhD
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lead on, plan, develop and conduct individual and/or collaborative research objectives, projects and proposals either as an individual or as part of a broader programme. To acquire, analyse, interpret
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Discover your career The world of the University of Nottingham is defined by our people and the values we share. Our environment is an ambitious vision brought to life across vibrant and forward
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purposes. We are looking for a confident, organised researcher who can evidence: • A PhD, or equivalent in mathematics, theoretical physics or a relevant branch of engineering. • OR near to completion
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-based role focusses on electromagnetic design, computational modelling (e.g., COMSOL, CST, ANSYS), dielectric characterisation, and testing that help to bridge the gap between laboratory-scale research
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. This project is sponsored by an industry partner and has set milestones and deliverables. Candidates must hold a PhD (or close to completion) in a relevant field such as brewing science, malting science, yeast
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entitled “White Matter Computation: Utilising axonal delays to sculpt network attractors”. The central aim of the project is to determine how dynamic patterns of neural activity evolve in a complex network