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Job Purpose Working with the Schools’ Programme Team Leader to coordinate the University WP Schools’ Programmes and ensure their effective and efficient delivery to c. 5,000 S4-S6 secondary school
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of cells. Our computational team supports the research activities of both experimental and computational scientists within the CVR (https://cvr.ac.uk). The postholder will contribute to the analysis
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training programme or within 4 years full-time equivalent of completing their training programme are eligible to apply. Clinical work during the PhD will be limited to one day per week. Doctors and dentists
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Job Purpose To provide assistance and laboratory support to academic and student service users. Work will support the smooth and effective running of teaching laboratories in line with the College/Institute/School Strategy. Main Duties and Responsibilities 1. Provide knowledge exchange...
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computing. In the UK's 2014 independent research exercise, we were rated top in Scotland for research impact. PhD: 3-4 years full-time; 6-8 years part-time; Thesis of Max 80,000 words MSc (Research): 1-2
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well as national and international collaborators. This British Heart Foundation-funded project, based in the Fuller Lab, will develop parallel, novel strategies targeting Ca(v)1.2 for translation into new
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Computing, Software Engineering, Computer Programming or Engineering programming. B2 Understanding of Trusted Research Environments. B3 Knowledge of developing parallel software for high performance
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ecomorphological outcomes significantly parallel. As a next step, it is vital to dig more deeply into the molecular mechanisms driving these patterns. This project will examine replicate divergences into specialist
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metabolic disease, including type 2 diabetes (T2D), Non-alcoholic fatty liver disease (NAFLD) and obesity, collectively referred to as metabolic syndrome (MetS), has occurred in parallel with a global decline
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detection model to a more flexible unequal-variance model in a hierarchical Bayesian approach (Lages, 2024). Techniques used: Computational modelling, Bayesian inference, sampling and simulation techniques