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in the Department of Chemistry, University of Oxford, for a period of up to 3 years. The project involves the development of methods to use light to regulate transport of amino acids and to engineer
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of advanced X-ray methods to explore chemical, crystallographic and morphological changes that drive battery performance loss. You should possess a doctorate in a relevant engineering or physical science
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. They must work as part of a team, be willing to learn new methods and skills and persevere in case of discouraging results. The role will also include protocol development. The postholder is expected to be
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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
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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, attack surfaces
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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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learning approaches. You will develop novel, reproducible methods for analysing both structured and unstructured clinical data, generating insights into disease trajectories, predicting clinical outcomes
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methods in Python and similar environments is also essential. Informal enquiries may be addressed to Professor David Clifton (email: david.clifton@eng.ox.ac.uk). Only online applications received before
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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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difference in combatting antimicrobial resistance globally and changing international policy. We contribute significantly to basic knowledge of antimicrobial resistance and apply research methods to identify