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base, the partnership will bring together the University of Oxford’s expertise in statistics, mathematics, engineering and AI with industry scientists. Within the partnership, small research teams will
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an initially solid-like state firsts yields and starts to flow, and in particular on the statistical physics of how initially sparse plastic events in an otherwise elastic background then spatio
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: Statistical signal/image processing, deep learning, machine learning, neuromorphic computing Good communication skills and an appropriate publication record are essential. Solid knowledge of Python and C++ is
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experience: Essential criteria PhD in neuroscience, neuroimaging or related discipline. Experience and knowledge of performing functional MRI experiments Proficiency in the use of statistical packages (e.g. R
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with experimental collaboration to uncover complex biological mechanisms. Our interdisciplinary work draws on statistical physics, applied mathematics, and close ties with experimental labs. Current
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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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University of Cambridge, Department of Pure Mathematics and Mathematical Statistics Position ID: CambUK -RESEARCHASSOCIATE [#26302] Position Title: Position Type: Postdoctoral Position Location
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Machine Learning, Human-Computing Interactions, Social Sciences, and Public Health. Applicants should hold, or be close to completion of, PhD/DPhil with research experience in computer science, statistics
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development. The ideal candidate will have a PhD in a relevant biological subject, together with experience in molecular biology, cell biology and immunology. Familiarity with flow cytometry, vascular biology
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development. The ideal candidate will have a PhD in a relevant biological subject, together with experience in molecular biology, cell biology and immunology. Familiarity with flow cytometry, vascular biology