844 web-programmer-developer "https:" "https:" "https:" "https:" "https:" "Newcastle University" positions at University of Oxford
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Building . This exciting development provides exceptional research and teaching facilities along with space for public engagement and outreach. It also offers renewed commitment to work across disciplinary
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explain how you meet each one. CVs alone will not be considered. We aim to provide a supportive working environment and are happy to discuss training and professional development opportunities. The Chair
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, as well as evidence of a substantial and realisable research plan which will complement the department’s research strategy. You will bring experience in public health practice, education, and research
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collaborations, enabling high-impact research into virus–host interactions and mechanisms relevant to global health challenges. You will manage your own research portfolio, developing and refining biochemical and
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(Research) and the Pro-Vice-Chancellor (Innovation), the postholder will lead – and contribute to the ongoing development of – a key University professional service, whose mission it is to advise and support
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funded by UKRI and is fixed-term to 31 December 2026. This is an on-site position only. The project aims to develop a computational model for biodegradable polymers degrading in water under mechanical
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solutions - and join a diverse, inclusive community that champions your wellbeing, development, and aspirations. Apply now to become part of our extraordinary legacy. What We Offer Working at the University
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, as well as the continuously developing landscape of graduate education and research, we are proud of the office’s versatility and its ability to work as a team in an ever-changing environment
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” and “wet” lab workflows). You will be able to Design, develop and implement algorithms and systems based on foundation models, large language models and/or AI agents for automated scientific discovery
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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