187 web-developer-university-of-liverpool Postdoctoral positions at University of Oxford
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Pay Scale: STANDARD GRADE 7 Salary (£): £41,997 to £46,913, salary inclusive of a pensionable Oxford University Weighting of £1,500 per year (pro rata for part time appointments) Location
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will employ a multi-disciplinary approach, including protein/nucleic acid biochemistry, bacterial genetics, and phage biology to test and generate hypotheses. You will develop new ideas and approaches
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base, the partnership will bring together the University of Oxford’s expertise in statistics, mathematics, engineering and AI with industry scientists. Within the partnership, small research teams will
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calculations and Brownian Dynamics simulations. The group is looking for a highly motivated and driven postdoctoral researcher to contribute strongly to a wave of ongoing developments deploying this technology
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on the electrosolvation force under development in the group. The planned investigations are primarily experimental in nature, but will proceed in close conjunction with insight from theory and simulations. The ideal
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to determine the activators of inflammation in atherosclerosis. You will identify and develop suitable techniques, and apparatus, for the collection and analysis of data (e.g. flow and mass cytometry, confocal
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potato and wheat. The post holder will be a member of a collaborative research consortium involving academic and industry partners. There will be opportunities for personal development, mentoring with
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The University of Oxford is a stimulating work environment, which enjoys an international reputation as a world-class centre of excellence. Our research plays a key role in tackling many global
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, to work on the EPSRC funded project “Prototyping a new green ammonia synthesis process using water, air and concentrated solar energy” in collaboration with Prof. Laura Torrente-Murciano, at the University
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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