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Field
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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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to a large-scale, interdisciplinary research programme. We are looking for someone with proven expertise in a fast-paced environment, who is committed to delivering high-quality research support and
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flexible working hours, remote/hybrid and/or part-time work (upon agreement). Inspiring working atmosphere: You are a part of a vibrant department with a big international community of other post docs and
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approaches which range from local micro-histories to large-scale quantitative analysis. We particularly value conversation between scholars of different periods and places, with different approaches. We also
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, working with some of the world’s largest single-cell data assets, and in the context of the world’s largest longitudinal population studies, many hosted here at the Big Data Institute, as well as other
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(myofiber) handling Experience in handling, processing, analysing and interpreting large data sets Experience in mentoring, leading and organising junior laboratory members and laboratory arrangements (e.g
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individual who will be responsible for recruitment and data collection in the final work package of the ICALD programme: a randomised trial with stepped wedge design evaluating the delivery and implementation
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About the role Working on a UK–Brazil project, you will advance next‑generation optical (flash & high‑power LED) and inductive thermography to assure the reliability of large composite wind‑turbine
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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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to prevent and/or mitigate the impact of E. coli and Klebsiella spp. infections, including those associated with antimicrobial resistance (AMR). As part of this post there is an opportunity to analyse large