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) data Genetic epidemiology and Mendelian randomisation studies (with support from senior scientists) Undertake meta-analyses. Conduct meta-analyses in R or Python across a range of cardiometabolic topics
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include tools such as Python, R, API-based data extraction, web scraping, bibliometric analysis, machine-assisted coding, and advanced qualitative platforms (e.g., NVivo, MAXQDA, AI-assisted workflows
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, and reinforcement learning) and end-user piloting of software systems - including technical attributes and legal/commercial considerations. Strong knowledge of Python and experience with machine
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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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calibration and artefact mitigation. · Develop and maintain reconstruction and data-processing pipelines using Python programming tools. · Implement quantitative 3D analysis workflows such as
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Engineering, Information Technology, Civil Engineering or a closely related discipline. Proficiency in Python for data processing, automation, and API integration. Demonstrable experience working with AI tools
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related discipline with a First Class or 2:1 Honours degree. Strong programming skills (Python essential). Experience with machine learning frameworks (e.g., PyTorch, TensorFlow). Experience with Large
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., PsychoPy, E-Prime, Gorilla, Presentation). Hands-on experience in data visualization, data analysis, and programming in R and/or Python. Experience in, and aptitude for, complex statistical modelling (inc
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-end language (e.g., Mode.js/JavaScript, Java, Python, C#, or similar). Front-end development experience using modern frameworks (e.g., React, Angular or similar). Understanding of software architecture
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research environments are essential. Proficiency in ArcPro, Python and a solid grasp of planetary geological processes, especially those relevant to Mercury, will be key to your success in this role