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supervision. Experience in Stata is essential and experience with R and/or Python desirable. We are looking for someone with fluency in written and spoken English, with excellent written and verbal
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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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and innovation (R&I) ecosystem. This is a unique opportunity to establish or expand your research programme in the UK, collaborate with world-class researchers, and contribute to national and global
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ability to think critically about scientific analysis in order to ensure robust results Computational skills to include experience of using a statistical package (e.g., R, MATLAB or Python) Ability to work
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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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to analyse datasets Experience in statistical or scientific programming (ideally R and/or Python) Experience in analyzing large and/or complex datasets Interest in quantifying uncertainties for computer models
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to the challenging problem of rearrangement scattering in molecular matter-antimatter collisions. We will develop and apply the R-matrix method to systems such as molecular hydrogen ion interacting with an antiproton
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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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economic studies funded by the UK National Institute for Health and Care Research. Experience of conducting economic evaluations using suitable statistical software (e.g. STATA, R or SAS) is essential
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, computer science, statistics, or a related field together with strong programming skills in Python, R, or similar languages, and proficiency in high-performance computing. You will have experience in large-scale