290 computer-programmer-"https:"-"UCL"-"https:"-"https:"-"https:"-"https:" Postdoctoral positions in United Kingdom
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training of mice, in vivo two-photon imaging, viral circuit tracing, and computational analysis to study how fronto-sensory feedback microcircuits contribute to adaptive cognition. The successful applicant
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researchers in the Future of Food programme at the Oxford Martin School. You must hold or be close to the completion of a doctoral degree in a relevant field (e.g. data science, industrial ecology, geography
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. The project combines behavioural training of mice, in vivo two-photon imaging, viral circuit tracing, and computational analysis to study how fronto-sensory feedback microcircuits contribute to adaptive
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level in the relevant subject area for the research programme; with a productive track record and have experience covering the full range of duties required. About the Institution The Faculty of Medicine
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degree and PhD (or close to completion) or research qualification/experience equivalent to PhD level in the relevant subject area for the research programme; with a productive track record and have
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created School within the Faculty of Humanities and Social Sciences. It has a range of both undergraduate and postgraduate programmes, including programmes that are jointly run with other Schools
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programmes involving national and international partnerships, often with our department acting as the lead site in multi-centre collaborations. We have been identified as the leading schizophrenia research
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programmes involving national and international partnerships, often with our department acting as the lead site in multi-centre collaborations. We have been identified as the leading schizophrenia research
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Hopkins University (USA). About the role The PDRA will lead the development of new computational and mathematical models to quantify and predict infectious disease risk, particularly for identifying high
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, economics, and other areas of computational social science; • AI scientists for natural science, integrating LLM agents with simulation and, where appropriate, robotic experimentation (e.g., automated “dry