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An exciting opportunity is available for a talented researcher to join the large and successful School of Health Sciences at the University of Southampton. You will join a multidisciplinary team who
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computational materials science techniques (DFT, MD, machine learning force field modelling) with data-driven approaches. Work with team to design and implement high-throughput experimental workflows for rapid
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decades, as well as registry data linked to multiple large surveys with longitudinal individual-level data, school-level aggregated data, and genetic data. The successful candidate is expected to use state
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lab group meeting (journal readings, in progress research talks, visiting speakers), and helping affiliated PhD and undergraduate students gain access to and work with the Cebu data. The Postdoc will
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the SG100K team to shortlist participants for recruitment Run focus groups to get user feedback on procedures and concerns Check data flows, analyze the data to inform future large-scale implementation Write
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multi-centre observational studies involving longitudinal clinical data and biological sample collections (e.g. Biomarkers and Stratification To Optimise outcomes in Psoriasis (BSTOP) study, mySkinomics
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a multidisciplinary team under the guidance of Brijesh Dongol (PI) and Gregory Chockler (co-I), as well as a large team of academics (Imperial, Kent, Sheffield, MPI-SWS, Cornell, IMDEA, etc) and
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candidate should have prior knowledge of quasi-experimental methods and, preferably, large data sources such as register data. The research fellow must take part in the faculty’s approved PhD program and is
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Stig Brøndbo 15th May 2025 Languages English English English Faculty of Science and Technology PhD Fellow in skill adaptations for remotely controlled and autonomous ship operations Apply
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longitudinal clinical data and biological sample collections (e.g. Biomarkers and Stratification To Optimise outcomes in Psoriasis (BSTOP) study, mySkinomics study, as well as interventional studies, e.g. PLAN