12 web-programmer-developer-"https:"-"https:" Fellowship positions at KINGS COLLEGE LONDON in United Kingdom
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professionals and research scientists. Based across King’s Denmark Hill, Guy’s, St Thomas’ and Waterloo campuses, our academic programme of teaching, research and clinical practice is embedded across six
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already commenced training in general cardiology and wish to gain more sub-specialty experience in Cardiac MRI (CMR), by taking an Out-Of-Programme Experience (OOPE) from their current training programmes
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program grant, REFUEL-MS, which is developing and evaluating a tailored digital treatment to help individuals with multiple sclerosis effectively manage their fatigue. You will be involved in analysing data
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already commenced training in general cardiology and wish to gain more sub-specialty experience in Cardiac MRI (CMR), by taking an Out-Of-Programme Experience (OOPE) from their current training programmes
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which is one of the largest and most comprehensive clinical liver programmes in the world. There are 5 focus areas: Steatotic liver disease, Cirrhosis & gut-liver axis, Hepatobiliary neoplasia
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of genome organisation and metabolic control - with the bold vision of building synthetic life. In this role, you will develop and apply deep learning methods to analyse single-cell modalities, focusing
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an a fixed term contract until 14th September 2026 (with potential to extend and develop a PhD depending on funding and progress) Research staff at King’s are entitled to at least 10 days per year (pro
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The position is funded by the Open Philanthropy grant “Verifiably Robust Conformal Probes”. The project’s goal is to develop methods for latent probing (aka activation monitoring) of large language models (LLMs
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development. This entitlement, from the Concordat to Support the Career Development of Researchers , applies to Postdocs, Research Assistants, Research and Teaching Technicians, Teaching Fellows and AEP
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of genome organisation and metabolic control - with the bold vision of building synthetic life. In this role, you will develop and apply deep learning methods to analyse single-cell modalities, focusing