354 postdoc-parallel-computing positions at University of Sheffield in United Kingdom
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progress and initiate and implement relevant programme of research. Disseminate research findings/results through the production of papers for high quality journals and presentation either in-house or
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, transcriptomics arrays and serological assays will be exploited to investigate biomarkers in cultured cells (primary supervisor). Field work at the Malawi Liverpool Wellcome Trust Clinical Research Programme will
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large research portfolio, it has extensive experimental, computational modelling and prototyping facilities. The candidate will benefit from working within a large, multi-disciplinary research group, and
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that operate with minimal computing, sensing, and actuating resources—essential features for implementation in real-world scenarios. To this end, we will leverage sophisticated mathematical tools such as
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as a low carbon, safe and abundant source of futureelectricity production. The UK Atomic Energy Authority (UKAEA) fusion research programme and a growing fusion supply chain are leading a world-wide
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Overview We have the opportunity for recent or upcoming University of Sheffield graduates to join the Lead Generation team within UK Student Recruitment and Events. Recruitment Interns sit within the Lead Generation team and deliver student recruitment activity in the North of England: Yorkshire...
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academic departments regarding concerns about student mental wellbeing via Mental Health Guidance and Liaison Desk. Maintain accurate and timely records on a computer system, working in accordance with
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an inclusive values base which promotes trauma informed practice, recovery, and recognizes and respects diversity. Maintain accurate and timely records on a computer system, working in accordance with
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manufacture, in experimental techniques, characterisation and computational modelling. In particular, you will gain experience in electrode manufacturing techniques, electrochemical characterisation, particle
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Early-stage failure prediction in fusion materials using machine learning