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targets. You will take a lead on development of computational approaches to integrate multi-omics data from patient samples, including DNA methylation, histone modifications, single-cell transcriptomics and
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networks. The research will employ mathematical modelling and computer simulation to identify synaptic plasticity rules which enable effective learning in large and deep networks and is consistent with
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Responsibilities, Accountabilities or Duties · Conduct and support research within the STAMPEDE imaging framework. This will involve the collection and management of large clinical data and samples for biomarker
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completion) relevant to research area (immunology). Expertise in flowcytometry and/or fluorescent microscopy. High level of analytical capability, especially in the understanding and analysis of large data
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large datasets C3 Theoretical and practical knowledge of sleep/chronobiology and related analysis techniques and/or mental and physical health data C4 Research creativity and cross-discipline
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, large-grant project on the epidemiology of bovine tuberculosis in wild badgers, using state-of-the-art Bayesian modelling approaches to study the drivers of infectiousness and transmission of infection in
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experience in data management, analysis, and visualisation. You will demonstrate experience working with large-scale biological datasets, preferably from biobank studies (e.g., UK Biobank, China Kadoorie
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with a range of stakeholders including consortium members working virtually, those in practice and members of the public with lived experience. • gathering and analysing rich qualitative data (from
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analyst for an ARC South London study on multi-morbidity in children using CPRD data. The ARC South London Children’s and Young person theme is important as many children in south London experience high
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will generate a wide range of contemporary high-resolution next-generation sequencing and array-based genomic and epigenomic datasets across large cohorts of human tumours and experimental models