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, large-grant project on the epidemiology of bovine tuberculosis in wild badgers, using state-of-the-art Bayesian modelling approaches to study the drivers of infectiousness and transmission of infection in
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completion) relevant to research area (immunology). Expertise in flowcytometry and/or fluorescent microscopy. High level of analytical capability, especially in the understanding and analysis of large data
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analyst for an ARC South London study on multi-morbidity in children using CPRD data. The ARC South London Children’s and Young person theme is important as many children in south London experience high
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collaboration that has mapped emotional hotspots in four cities in the UK and EU using spatial analysis of social media data. The next phase of the project aims to incorporate explainable AI (XAI) to interpret
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using CPRD data. The ARC South London Children’s and Young person theme is important as many children in south London experience high levels of poor health, and unequal health and care outcomes. We
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model fitting, including Bayesian model fitting, is desirable but not essential. Familiarity or experience of management and analysis of large multidimensional real world data sets using Stata, R, Python
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, development, implementation, and coordination of research and laboratory protocols to investigate transmission of enteric pathogens in low-income households of Salvador, Brazil within the context of large-scale
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to contribute to a world-leading project on Survey Data Collection Methodology Survey Futures https://surveyfutures.net/ . Survey Futures is a collaboration between nine universities and three survey
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the direction of Dr Maslovskaya, you will be part of a large multi-institution team of survey data collection methods experts in the UK. You will analyse probability-based NatCen online panel data collected using
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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