140 high-performance-computing-postdoc Postdoctoral positions at University of Oxford
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Hyundai Motor Group, the Centre is led by Oxford strategy faculty Rafael Ramirez (Director) and Trudi Lang. (Co-Director). Focusing on a discrete set of high-impact themes, the Centre contributes
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anxiety, to work within the established research programme. Substantial hands-on research and professional experience of working with individuals with mental health difficulties, including first-hand
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imaging and spectroscopy. Experience with data analysis or the ability to perform basic biochemical work with proteins and DNA, e.g., fluorescence labelling, enzymatic reactions will be highly rated in
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learning, at the intersection of reinforcement learning, deep learning and computer vision, in order to train effective robotic agents in simulation. You should hold a relevant PhD/DPhil (or near completion
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methods suitable for legged systems in physically-realistic simulated environments and on real robots. You should hold or be close to completion of a PhD/DPhil in robotics, computer science, machine
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the Department of Engineering Science at the University of Oxford. The post is funded by the Oxford Martin Programme on Circular Battery Economies. It is fixed term up to December 2027. You will undertake
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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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Metabolism (OCDEM) on studies related to circadian rhythms in population health. This post is part of a large, interdisciplinary research programme, offering attractive opportunities to work across
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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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explores novel aggregation methods at the intersection of AI safety, computational social choice, and judgment aggregation, aiming to formally integrate multi-stakeholder preferences into AI system design