41 parallel-computing-numerical-methods-"Simons-Foundation" research jobs at University of London
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empirical research. They will oversee specific research tasks, develop new techniques, and generate original contributions to the programme while fostering a collaborative team environment. Key
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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 study in collaboration with research teams at Nottingham, Oxford, UKHSA and Manchester with expertise in mixed-method policy evaluation, antimicrobial resistance, pharmacy practice research, primary care
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on Black holes and Strong Gravity (SimonsC-BHSG). The Postdoctoral Fellowship is intended for work on numerical studies of non-linearities with SimonsC-BHSG Co-PI Katy Clough. The successful applicant should
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resulting datasets using statistical and computational tools. They will also contribute to molecular workflows including DNA/RNA extraction, qPCR and sequencing preparation, and support cellular immunology
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to work on a project investigating mechanosensing in flies (Diptera). This post will focus on using detailed wing geometry models and free flight kinematic measurements in computational fluid and structural
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About the Role The purpose of this role is to provide mixed methods and evidence synthesis research support for a Gates funded project examining the utility of iron preparations for maternal anaemia
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exciting project that will develop new approaches to handle missing data in statistical analyses based on machine learning methods. The Research Fellow will be based in the Department of Medical Statistics
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programme. Around one third of young people experience elevated suspicious thoughts and paranoid ideation. “Treating Unhelpful Suspicious Thoughts in teenagers (TRUST): A schools-based feasibility randomised
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to work with an international team on developing cutting-edge novel demographic, statistical and computational methods in estimating, modelling and forecasting measures of health, well-being, and human