22 web-programmer-developer-"https:"-"UCL"-"CEA-Saclay" "https:" Fellowship positions at KINGS COLLEGE LONDON
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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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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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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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term contract of 13 months from contract start date. Research staff at King’s are entitled to at least 10 days per year (pro-rata) for professional development. This entitlement, from the Concordat
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developers, administrative staff, and clinical leaders—to support implementation, deliver training, and provide ongoing assistance to end-users. Strong digital and IT competence is essential, particularly
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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