125 parallel-computing-numerical-methods Postdoctoral positions at University of Oxford in United Kingdom
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discoveries on the electrosolvation force. The project will use a range of optical methods to examine the interactions in colloidal and molecular systems and relate the experimental findings to theories
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on single-agent settings. We are seeking a highly motivated postdoc to conduct research into this fast-moving area. Directions may include investigating quality evaluation methods for multi-agent systems
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cryo-EM, cryo-ET, FIB milling, and biochemical methods to understand mechanisms of dynein-2 transport, building on recent advances in the group (NSMB 2017 PMID 28394326; NSMB 2019 PMID: 31451806; Cell
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cryoEM and cryoET you will ideally have background in at least one of these methods. You also should have a deep interest in mechanisms underlying basic biological processes at the molecular level
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of agentic behaviour and publishing high-impact research. Candidates should possess a PhD (or be near completion) in PhD in Computer Science, AI, Security, or a related field. You will have a Strong background
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PREVIOUS APPLICANTS NEED NOT TO APPLY! We are seeking to appoint a Senior Postdoctoral Researcher in Genomics of Myeloid Disorders to join the computational genomics group led by Prof Schuster
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quantitative methods will be highly valued, but such skills are not essential. The postholder will be a member of the Saïd Business School’s research community with access to internal research seminars and other
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methods to study human bone marrow models using high content imaging approaches. You will lead in designing and establishing new protocols to the laboratory as well as supporting, mentoring and training
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Oxford’s Department of Orthopaedics (NDORMS) as well as collaborators in Bristol and Cardiff. You should have a PhD/DPhil (or be near completion) in robotics, computer vision, machine learning or a closely
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A postdoctoral research associate position is available for a technically strong researcher to join the Oxford Machine Learning in NeuroImaging (OMNI) lab at Oxford’s Department of Computer