95 computational "https:" "https:" "https:" "https:" "https:" positions at University of Sheffield
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Program Director Dr Simon Curran. The Academic Training Lead for Nephrology is Dr James Fotheringham. Furtherdetails of the NIHR IAT pathway can be found at: https://www.nihr.ac.uk/explore-nihr/academy
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For further information about the Academic Clinical Lectureship programme, please visit https://www.nihr.ac.uk/career-development/research-career-funding-programmes/postdoctoral/clinical-lectureship Information
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projects. Undertake (Grade 7) or contribute to (Grade 6) methodological research in systematic reviewing and evidence synthesis. Contribute to our teaching programme, including delivering lectures, tutorials
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through their programme. The ideal candidate will have outstanding customer service and interpersonal skills, and an ability to put people at ease through sophisticated and sensitive verbal and non-verbal
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Reliable and Efficient Adaptation of Large Language Models School of Computer Science PhD Research Project Directly Funded Students Worldwide Dr Cass Zhixue Zhao, Prof Nikos Aletras Application
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. The project is funded by an EPSRC research programme aimed at advancing the theoretical and experimental understanding of spin polarisation physics and improving the performance of hyperpolariser systems used
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the UK must close, and turning that into the knowledge infrastructure a national programme runs on. A research theme of your own is developed alongside that work, not instead of it. This post focuses
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developing, revising and updating programme content and delivery, and ensuring compliance with quality standards, regulations and accreditation requirements. Demonstrate continuing professional development in
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to work in the UK, you can find more information here to help determine your visa eligibility. Additional guidance is also available on the UK Visa & Immigration website . Our website https
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computational text processing, natural language processing and large language models. Main duties and responsibilities Develop an automated pipeline for the data collection, cleaning and processing of scientific