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considerations. Strong knowledge of Python and experience with machine learning libraries (Scikit-learn, TensorFlow, PyTorch). Industry experience in supporting/leading/training software development and AI
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theoretical basis. Practical, demonstrable experience in: R, Bioconductor, Python, Java, DNA/RNA alignment software (e.g. BWA, Minimap), variant calling methodologies (e.g. GATK Toolkit, hmftools, long read
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. Understanding of next generation sequencing datasets, including their structure and theoretical basis. Practical, demonstrable experience in: R, Bioconductor, Python, Java, DNA/RNA alignment software (e.g. BWA
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or more of the following FastAPI, PostgreSQL and/or asynchronous workflows (Apache Airflow, Celery, RabbitMQ). 4. Significant experience in Python and experience using common software development
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activities, including supporting clinical trial and experimental medicine studies. You will select, follow, and adapt specialist data analysis methodologies using R and/or Python to work with large-scale
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to analyses, dashboards and automated validation/ETL pipelines using SQL/Excel and/or R/Python, support simple visualisations and reports for investigators. About you Experience extracting/abstracting data from
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in machine learning and/or advanced analytical methods, experience working with complex or large-scale datasets, and strong programming skills (e.g., Python or R). You will be able to communicate
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software (e.g. ArcGIS, QGIS) and coding environments (e.g. Python or R), collaborating across LUMHR themes, and supporting interdisciplinary research activity. Teaching support may be required, up to a
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, or computational social science Have good programming skills in at least one of: Python, Julia, Rust, C++ Be excited and inspired by the proposed project area Be a self-starter with a highly collaborative spirit
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related quantitative subject. Essential/important: Evidence of strong quantitative skills and interest in computational modelling. Basic programming/scripting ability (e.g., Python, MATLAB, Julia, C/C