177 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions at University of Oxford
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We are looking to appoint a postdoctoral researcher, to work with a group of UK Higher Education Institutions to deliver a programme of mental health research. The work is funded by the Medical
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with an international reputation for excellence. The Department has a substantial research programme, with major funding from Medical Research Council (MRC), Wellcome Trust and National Institute
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will be educated to PhD level with relevant experience in molecular plant biology and evolution and will work closely with other group members to assist them with gene functional characterisation
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interpretation of atmospheric circulation in high-resolution reanalysis data, idealised model simulations and a state-of-the-art weather forecasting system. The post-holder will have the opportunity to teach
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the UKRI through the Frontier Guarantee Programme to Dr Jani R Bolla. The work is to be conducted in his lab in the Department Biology, University of Oxford, South Parks Road, Oxford, OX1 3RB
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dynamics and (at intermediate redshifts) strong gravitational lensing, thus preserving and extending the team’s lead in this field. Applicants should have a PhD (or close to completion) in (Astro) physics
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annum inclusive of Oxford University weighting Potential to under fill at grade 06RS: £34,982-£40,855 per annum inclusive of Oxford University weighting The Department of Computer Science seeks to employ
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. The post-holder will have the opportunity to teach. Applicants should hold PhD in Astrophysics or a related field. A strong background in Radio interferometry observation and sufficient specialist knowledge
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will be required due to regulated activity involving children and ‘at risk’ adults. The successful candidate will hold, or have submitted a relevant PhD/DPhil (or equivalent) in a relevant discipline
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We are seeking a full-time Postdoctoral Research Assistant to join a cross disciplinary research project to improve our understanding of colorectal cancer. Deep learning has revolutionised image