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Associate with mathematical modelling and numerical/data analysis background to join our food system resilience project, led by University of Reading, joining a large interdisciplinary team with an excellent
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will involve two key components. First, the computational analysis of TCR repertoires generated from the blood of large numbers of cancer cases and matched controls. Second, the role will involve
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the bigger picture. You’ll have experience in data storytelling and visualisation, a keen eye for detail, and the ability to drive meaning from large datasets to generate clear, high-quality insight that makes
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candidate will be involved in analysing data from patients with psoriatic arthritis as part of a large international study funded by the European Union: Hippocrates. The work sets out to explore new standards
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work experience. You must also have demonstrable ability to write R code for data import & manipulation, a working knowledge of SQL, experience using/processing large or complex datasets and a meticulous
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for the efficient running of key administrative elements of this large-scale project, with strong supervision and support from an experienced team including the project manager. Providing some PA support (e.g. diary
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reward and recognition. Person Specification Demonstrable HR experience of working within a large, unionised, complex, and diverse organisation (HEI sector and Law School experience desirable). Exceptional
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of challenges of building large-scale systems. Programming skills in Python. A good Bachelor’s Hons degree (2.1 or above or international equivalent) and/or Master’s degree in a relevant subject (physics
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of a large multidisciplinary collaboration between LSHTM and Oxford Brookes University (lead partner), UCL, LSE, University of Leeds, University of Edinburgh, and a wide network of UK stakeholders
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or currently working towards a CCAB-recognised professional accounting qualification, with a proven track record of managing large data sets and reconciling complex financial records. We are UAL University