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surveys, early universe and gravitational physics. Good programming experience, an enthusiasm for coding and data analysis, and the ability to work in a large collaboration, are particularly relevant
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including cell culture, organ-chip models, tissue engineering, and musculoskeletal biology. The PDRA will plan and conduct experiments, generate high-quality data, prepare publications, make presentations and
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statistical and computational methods designed to use “big data” and to address questions of direct or indirect relevance to common complex diseases and disorders. The appointee will join the group of Professor
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include undertaking research, as appropriate, to support the project including contributing to the delivery and analysis of a large-scale questionnaire survey, conducting qualitative research interviews
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research environment supported by a team with broad expertise in data science, infectious diseases, hepatology, and clinical informatics. You will take a leading role in analysing large-scale, longitudinal
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further including to automated platforms to generate large statistical data sets. We will also experiment with untried higher spatial resolution techniques. The large, multi-dimensional data sets will be
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Experience in statistical or scientific programming (ideally R and/or Python) Experience in analyzing large and/or complex datasets Interest in quantifying uncertainties for computer models and/or climate
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be finalised by July 2026. Supported Areas for START Infocomm Technology Information Security: Mobile security, cyber-physical systems, IoT security, security analytics, operational cybersecurity
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candidate must have experience in the following areas: molecular cell biology, plant phenotyping, and image/data analysis, as well as working as part of a large team. A track record of publishing research is
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statistical and computational methods designed to use “big data” and to address questions of direct or indirect relevance to common complex diseases and disorders. The appointee will join the group of Professor