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-performance or cloud computing environments. Need strong data management and database skills, expertise in clinical phenotyping ontologies and the application of machine-learning/AI methods to biomedical data
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the use of computing servers Desirable Criteria Experience fine-tuning large language models (e.g., BERT, BioGPT, MedPaLM) for clinical NLP tasks. Experience with cloud or distributed computing environments
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. The successful candidate will work within a multidisciplinary team to unravel the metabolic drivers of HCC biology and transplant rejection through cutting-edge spatial multi-omics and computational metabolic
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Hopkins University (USA), and Google Deepmind (London).* About the role The PDRA will lead the development of new computational and mathematical models to quantify and predict infectious disease risk
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the Department of Informatics, part of the Faculty of Natural, Mathematical & Engineering Sciences (NMES). The department is internationally recognised for its contributions to robotics, AI, and human-centred
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Mental Health Younger Generations Programme. You will work with a friendly, supportive, passionate, and hard-working group to undertake statistical analysis of quantitative data to test hypothesis
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About us The Faculty of Natural, Mathematical & Engineering Sciences (NMES) comprises Chemistry, Engineering, Informatics, Mathematics, and Physics – all departments highly rated in research
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in a computational model of paranoia may be influenced by THC administration or in support-seeking participants under sober conditions. The postholder will collect a range of psychopharmacology
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Salary Details The starting salary will be from £34,610 on Grade E, depending on qualifications and experience. The above full-time post is available from 2 February 2026 to 2 August 2027 on a fixed-term basis in the Faculty of Environment, Science and Economy. The post The Faculty wishes to...
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, computer-aided decision support systems Previous experience with using deep learning models (e.g., convolutional neural networks, autoencoders, transformers) for academic research Documented experience in