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specialist knowledge in mechatronics design and control, and proven programming experience in Python, MATLAB or C/C++. Informal enquiries may be addressed to Professor Liang He (email: liang.he@eng.ox.ac.uk
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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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systems modelling including technical knowledge (e.g., in data science, input-output modelling, applied economic modelling, environmental and ecological assessments, GIS, comparative risk assessments), as
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strong programming skills, particularly in Python. Good interpersonal skills and the ability to work as part of a team are essential in order to make a strong contribution to the project. Benefits
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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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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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methods in Python and similar environments is also essential. Informal enquiries may be addressed to Professor David Clifton (email: david.clifton@eng.ox.ac.uk). Only online applications received before
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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
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atmospheric physics, meteorology, climate, numerical methods, and data science. The Research Associate will be proficient in programming/scripting (e.g., in Python, and/or R, and/or Matlab, and/or Bash script