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interpretation. This role will involve working closely with civil engineers, computational modellers, Physicists, and geophysicists to translate raw sensor outputs into actionable insights. Role Summary Lead data
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research project on cardiovascular risk prediction for people with immune-mediated inflammatory disease. The successful candidate will use advanced risk prediction methods to develop prediction models
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electronic health records) and developing computational models. Establishes frameworks for data modernization, integrating metadata and varied datasets to create databases suitable for cross-disciplinary AI
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modelling will be useful for evaluating these options. To that end, this team will develop a novel analytical simulation framework and use it to address these pressing questions, in close collaboration with
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Maria de Maeztu . All positions are funded for up to 3 years. The three scientific profiles are as follows: Position in Beyond the standard models of cosmology and particle physics Position in
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, and semi-structured interviews. Using European competence models (e.g., GreenComp, LifeComp), the project will develop flexible lifelong learning models that universities can adapt to different
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modelling of climate-sensitive infectious diseases, with a particular emphasis on Bayesian hierarchical modeling using Integrated Nested Laplace Approximation (INLA). The work will contribute to ongoing
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that are at the intersection of aging and heart failure that may translate into novel therapeutic strategies. Our research employs a comprehensive array of models and methodologies, including molecular biology, cell lines
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, glioblastomas, colon cancer, and lung cancer. Advancing precision oncology through machine-learning models: We integrate multimodal patient data, including multiomic data and health record information, to develop
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date for the post) Experience in maintaining stem cell culture models, with preference for mouse or human ESCs. Experience in high-throughput (epi)genomics assays or related technologies. Experience in