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to) fundamental research in machine learning or statistics, algorithm design, the application of AI methods in science, healthcare, social sciences, or business. You should have a PhD or equivalent level of
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will a have a relevant PhD and medical degree alongside registration with the GMC at Specialist Registrar Garde or below. You will have a recent track record in histopathology and use of machine learning
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annotation of these metabolomes using multistage fragmentation (MSⁿ) data, incorporating novel computational methods and strategies (e.g. spectral matching, network-based approaches, machine learning) where
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Strong analytical skills and experience in developing and implementing machine learning/AI solutions using relevant languages and frameworks Excellent communication skills and proven ability to collaborate
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using hybrid models combining mechanistic, GenAI, and machine learning approaches. You’ll contribute to building disease-specific Digital Twins using large-scale single-cell multi-omics datasets
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in statistics, machine learning, mathematical modelling, or a related field, to join our research team in the Department of Applied Health Sciences. The successful candidate will work on an NIHR funded
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. The Department seeks candidates with interests in Statistical research at the interface of machine learning and AI. They will have the skills and enthusiasm to lecture graduate level, over a wide range of topics
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strong analytical skills and desirably some computer modelling experience, and an ability to work in a multidisciplinary team and engage confidently with partners. You will have a track record of
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seeks candidates with interests in Statistical research at the interface of machine learning and AI. They will have the skills and enthusiasm to lecture graduate level, over a wide range of topics within
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time role, 0.1FTE. The activities of this role will support development of future proposals for funding, into AI for renewable energy. You will consider ways in which the integration of machine learning