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Job id: 123465. Salary: £39,076 - £43,909 per annum, including London Weighting Allowance. Posted: 26 August 2025. Closing date: 09 September 2025. Business unit: IoPPN. Department: Developmental Neurobiology. Contact details:Dr. Sadra Sadeh. sadra.sadeh@kcl.ac.uk Location: Denmark Hill...
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symbiosis of cutting-edge AI combined with human support. The successful candidate will partake in the development of personalised, context-sensitive Large Language Models (LLMs) for health coaching. By
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of a Faraday Institution funded project on battery fire modelling, specifically focusing on thermal runaway and cell-to-cell propagation of flaming combustion. The role-holder will be part of a larger
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of the land ice contribution to sea level rise until 2300 with machine learning. You will develop probabilistic machine learning “emulators” of multiple ice sheet and glacier models, based on large ensembles
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split 0.5FTE on the UKRI Medical Research Council funded project STARS: Sharing Tools and Artefacts for Reproducible Simulations in healthcare ; and 0.5FTE on the Health Service Modelling Associates (HSMA
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expertise in analysing/ training models on biological or chemical datasets Proficiency in Python for data science and machine learning Possess sufficient breadth or depth of specialist knowledge with deep
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and Care Excellence (NICE) and other leading agencies. Depending on your level you will: GRA: Support cost-effectiveness aspects of health technology assessments (HTAs), analysing economic models
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, democratising access to data, AI assets, technologies, and capabilities. PharosAI unites large-scale multimodal cancer datasets with AI models through a highly-secure, trusted, federated platform, offering state
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morphogenesis and the action of morphogens. We use animal models to investigate the physical morphogenesis of tissues. It is part of the vibrant and supportive environment of the Centre for Craniofacial
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vivo assays with human serum samples (HTA certification required), and in vivo models to study the dynamics of infection. The successful candidate will be supported in applications for PhD studentships