175 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions at University of Oxford
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properties at an atomistic, electronic and structural level. Applicants should possess or be close to obtaining a PhD in physics, materials science, or physical chemistry. They should be highly experienced in
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these processes, with the aim of understanding how ageing promotes CH progression. You will hold a PhD within the area of molecular biology or have thesis submitted at time of application, and will have experience
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. You will be responsible for managing your own academic research, collaborating with computational and clinical researchers, and contributing to the scientific development of the lab. This is an exciting
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applications. In this role, you will take the lead on an independent project within our broader research programme. Your work will centre on identifying and characterising novel regulators of the immune response
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of the project. Applicants should hold, or be close to completion of, PhD/DPhil in Biology or a related subject. You should have a high level of competence in cell biology and relevant experience demonstrated by
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to implantation, including validating methods in virtual in vivo environments. • Collaborate with engineers to refine fuel cell specifications and support in vivo experiments. You should hold a relevant PhD
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for differential rate correction). The successful applicant will hold, or be close to completion of, a relevant PhD/DPhil in bioinformatics, comparative genomics and phylogenetics, together with relevant experience
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As part of the Oxford Martin School Digital Pandemic Preparedness Programme and the Leverhulme Centre for Demographic Science (LCDS), Nuffield Department of Population Health (NDPH) are recruiting a
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; and organising and deliver autonomous system trials and demonstrations at internal and external sites. You should possess a relevant PhD/DPhil or be near completion together with relevant experience
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rhythms in population health. This post is part of a large, interdisciplinary research programme, offering attractive opportunities to work across conventional boundaries and pursue hypothesis-led science