575 parallel-computing-numerical-methods-"DTU" Fellowship research jobs in United Kingdom
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Field
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Fellow will be using Natural Language Processing (NLP) methods, with a special focus on generative Large Language Models (LLMs), to interrogate a very large sample of Electronic Health Records from people
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future development of an ongoing epilepsy research project funded by the UK Epilepsy Research Institute. The Research Fellow will be using Natural Language Processing (NLP) methods, with a special focus on
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ambitious plans to deliver an innovative research programme, positioning them to be future leaders in their field. For the Associate Professor and Professor roles, we expect applicants to be established
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/ developing research profile and/ or respected national/ international profile in mixed methods around human-computer interaction PhD or equivalent in relevant subject area or the equivalent in professional
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quality improvement skills along an academic pathway. The programme will train GP Fellows in health data science, research methods, and the clinical effectiveness approach, to develop them into future
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viral (AAV) vectors. We propose to compare the capabilities of this instrument with that of commercially available mass spectrometry platforms and other methods. As part of this exciting and truly
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Full Time Fixed Term for 2 years PhD in Computer Science/HCI or Related? Want to use your creative skills to help #makeNormalBetter 4all @scale? Come join the WellthLab The WellthLab mission is to
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Do you have a PhD in HCI, Computer Science, or Related? Interested in innovating interactive technologies to help #makeNormalBetter for all? Excellent and committed researcher? Come join the
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Research Fellow - OSMOSIS research programme Apply online Job number SHMS00480 School / Service School of Health & Medical Sciences Department Nursing Location Myddelton Street Building Contract
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to appoint a Research Fellow responsible for the day-to-day running of a NIHR-funded research programme, OSMOSIS - aiming to co-produce resources and toolkits to improve the support available to family