187 fully-funded-phd-program-computer-science-eth Postdoctoral positions at University of Oxford
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leading academic and industry experts, and an active academic/industry exchange program that aims to accelerate career development for the postholder employed on the project. About you The postholder should
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Engineering, Mathematics, Statistics, Computer Science or conjugate subject; strong record of publication in the relevant literature; good knowledge of machine learning algorithms and/or statistical methods
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relevant skills acquired and will also be determined by the funding available. About you Applicants will hold a PhD/DPhil or be near completion of a PhD/DPhil in a subject relative to Structural Biology
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projects. It is essential that you hold a PhD/DPhil in a quantitative or computer science related subject (e.g. Statistics, Machine Learning, Biostatistics, AI, Engineering), and have post-qualification
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We are seeking a creative and highly motivated postdoctoral researcher to join the Turing AI World-Leading Fellowship research programme led by Professor Alison Noble. This exciting and ambitious
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have completed, or be close to completing, a PhD/DPhil in a relevant quantitative field such as computational social science, computer science, or cognitive science. They will have a demonstrable track
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will have or be close to the completion of a PhD in Neuroscience, Psychology or a closely related discipline. With in-depth knowledge of cognitive and computational neuroscience including motivation
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audiences and an ability to work well independently using own initiative, as well as part of a team. Experience in a variety of advanced microscopy techniques and computational biology expertise are desired
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We are seeking a talented and motivated researcher to join the Mead Group to contribute to a major research programme, focused on understanding and preventing disease progression in
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We are seeking a talented and motivated researcher to join the Mead Group to contribute to a major research programme focused on characterisation of in vivo models of myeloid neoplasms and