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project focused on systematically exploring the impact of the exposome on complex disease risk, through the lens of multi-omics data (e.g., genomics, proteomics, metabolomics and biochemistry) from large
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close to completion, of a PhD/DPhil, together with relevant experience. You should have knowledge and practical experience in farm sustainability and feel confident working with large datasets and work with
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on proposing for, and analysing, data with VLBI arrays to study relativistic jets from black holes. They will work with other observers and theoreticians to develop our understanding of black hole jet formation
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on proposing for, and analysing, data with VLBI arrays to study relativistic jets from black holes. They will work with other observers and theoreticians to develop our understanding of black hole jet formation
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involve undertaking full time research in grid connected large wind energy system dynamic modelling, control and analysis. In particular, the objective of this research programme is to lay the foundations
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generations of research and development professionals, data specialists, technology experts, inventors, and scientists for industry and society. NANO group at the Department of Applied Physics, is seeking
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1 Oct 2025 Job Information Organisation/Company Imperial College London Department Electrical and Electonic Engineering Research Field Engineering » Electrical engineering Researcher Profile First
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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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for Research Staff Development for more information. About you To be successful in this role, we are looking for candidates to have the following skills and experience: Essential criteria A PhD in Humanities or
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will increase to Grade 6. Desirable criteria Experience with skeletal muscle tissue and single muscle cell (myofiber) handling Experience in handling, processing, analysing and interpreting large data