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economic modelling packages (such as STATA, R, WinBUGS) and the ability to undertake modelling of study data Experience of research on methodological aspects of economic evaluation and advanced evidence
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gained in matrix management within the context of the R&I roadmap for transformation, providing significant career development opportunities. This is an exciting, challenging and highly varied role which
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Subject areas of particular interest may include: Machine and Deep Learning Data Visualisation Generative AI and LLMs Programming (Python, R, SQL) Databases and IoT Applied Statistical Methods You will also
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their expertise in design engineering, digital simulation, and applied R&D. You’ll gain access to state-of-the-art facilities, tailored training support, and the potential for ongoing employment with the industrial
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package such as Stata/R. A commitment to multi-disciplinary and collaborative working is also essential. The ideal candidate would have experience using electronic health records for pharmacoepidemiologic
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tools (e.g. SPSS, R, NVIVO), mapping trail and community characteristics to understand how context affects outcomes. Furthermore, all of your skills and experiences in relation to research in the fields
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strong background in Biological Sciences, and a particular interest in biology. You will be experienced in using and teaching R Studio in a way that encourages and inspires students to embrace statistical
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Performance Computing, computational and cutting-edge data analytics methods, and growth and retention of vital capacity in research software engineering and technical R&D are at the core of this endeavour. We
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technologies/platforms (e.g., Salesforce, Marketo, HubSpot) Analytical skills and familiarity with tools for data analysis and visualisation (e.g., Tableau, Power BI, R, Python) General interest in Artificial
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July 2025 Reference 0525-119-R Right to work: Please note that it will not be possible for the University to issue a Certificate of Sponsorship to the successful candidate for this position. Therefore