17 development "https:" "https:" "https:" "UCL" "UCL" Fellowship positions at King's College London
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Classics Department is seeking to appoint an Early Career Development Fellow in Classics for a two-year period. The Fellow will conduct research, produce research publications, deliver teaching, and provide
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combined with human support. To learn more please visit https://www.kcl.ac.uk/research/embrace About the role The Research Fellow in Digital Health & Data Sciences is focused on the development and
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. Fellowships provide a competitive salary and up to £30,000 in research expenses for 18–24 months, enabling fellows to establish a distinctive research programme and prepare competitive applications
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, computer science, and the natural sciences to develop the conceptual and mathematical tools needed for the trustworthy deployment of AI agents in science. The project is based at the Egenis Centre for the Study of
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fixed term contract until 31st March 2030. We are seeking an experienced data and infrastructure specialist to lead the development of a national database supporting UK mental health research capabilities
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, and with expertise in quantitative and qualitative methods, to develop a training and capacity-building programme and lead research projects working on large datasets. On training and capacity-building
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to significantly grow the brain tumour research community in the UK, train outstanding health care professionals and offer better care for patients in the UK. About the role: This Post CCT Fellowship is for
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. They will take a proactive role in the conceptual and operational development and implementation of the A-STAR register and drive forward initiatives as well as implement strategies to achieve the project’s
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Location: The Francis Crick Institute, London Short summary Our lab aims to understand how functional organs are built during embryonic development, an important problem in biology with implications
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health. The post holder will develop innovative AI techniques approaches applied to oral healthcare, with a particular focus on Large Language Model-based multimodal data understanding and reasoning