61 phd-in-computer-vision-and-machine-learning Fellowship positions at University of Nottingham
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Applications are invited from qualitative researchers with a PhD (or close to completion) for the position of Research Associate/Fellow within the School of Health Sciences. You will be part of a
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of disseminating research findings (e.g., through journal publications and conferences). - Have a PhD in Psychology or a related discipline (the PhD thesis must be submitted prior to starting the position). What we
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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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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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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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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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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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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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must have an MSc or PhD in forensic psychology, or a related field. The project involves recruitment online using a detailed survey, and a video interview, in a small subset of the sample. Recruitment
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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