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shelves, the breakup of which can speed up flow of grounded ice and affect global sea level, and on the highly specialised Antarctic biodiversity. This ambitious programme brings together leading UK (BAS
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. The post-holder will be responsible for managing their own academic research programme in Salmonella effector biology. You will have a high degree of autonomy to develop the methodology and experimental
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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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programme grant with partners across the UK to facilitate the use of hydrogen for aviation, and in particular the icing vulnerability of heat exchangers and parts of the airframe. You will work to generate
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renewable award. You will lead a programme of research in the molecular mechanisms of cardiovascular disease, that may include a range of approaches including targeted genetic murine models, primary cell
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engineering, computer science or other field relevant to the proposed area of research. You should have a good track record of robotic publications/presentations in the field of healthcare, possess sufficient
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About the role We are seeking a full-time Postdoctoral Research Assistant to join the Hypersonics research group at the Department of Engineering Science, Osney. The post is fixed for 19 months with potential further extension, subject to confirmed funding. You will lead experiments in the OPG...
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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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computational workflows on a high-performance cluster. You will test hypotheses using data from multiple sources, refining your approach as needed. The role also involves close collaboration with colleagues
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with the possibility of renewal. This project addresses the high computational and energy costs of Large Language Models (LLMs) by developing more efficient training and inference methods, particularly