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have strong quantitative analysis skills, using statistical programming packages such as R, as well as excellent communication skills. This is a full time, fixed term post (part time considered) for 3
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the AM fungus, R. irregularis. The project focuses on obtaining a mechanistic understanding of EV biogenesis, cargo loading and signals that regulate EV release during the interaction. The post-doc will
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analysis of EVs isolated during the interaction of M. truncatula and the AM fungus, R. irregularis. The project focuses on obtaining a mechanistic understanding of EV biogenesis, cargo loading and signals
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strong potential o Proficiency in Python and/or R programming languages o Experience working in high-performance computing (HPC) environments o Command line proficiency and BASH scripting
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/or R) and understanding of Markov model principles. You will be based in the Gibson Building, Nuffield Department of Primary Care Health Sciences, Woodstock Road, Oxford, OX2 6GG as your normal place
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publications in high impact journals, advanced proficiency in R and Python, and prior experience in cardiac imaging and high-dimensional data integration are essential. The postholder will be expected to work
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experience developing reproducible machine learning pipelines applied to complex biological datasets also experience of coding in R and python. Applications for this vacancy should be made online and you will
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cell RNA-seq, ATAC-seq Experience with python and/or R programming languages, including single cell package ecosystems (scanpy and/or Seurat) Experience working within HPC environments Experience working
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with mouse genetics, molecular biology (including functional genomics) and bioinformatics (including UNIX, R and Python for single cell analysis). You will be highly motivated, current with
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/scripting (e.g., in Python, and/or R, and/or Matlab, and/or Bash script & NCO & CDO, etc.) and have demonstrable expertise in the analysis of big data, while the experience with interpretation of climate