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Brunel University of London was established in 1966 and is a leading multidisciplinary research-intensive technology university delivering economic, social and cultural benefits. For more information
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for cardiovascular disease in this patient group using linked electronic health record data. The post offers an excellent opportunity to develop expertise in risk prediction methodology for electronic health records
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for cardiovascular disease in this patient group using linked electronic health record data. The post offers an excellent opportunity to develop expertise in risk prediction methodology for electronic health records
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and big data mining. The research fellow will take a leading role in an EU-Africa research project, collaborating with Research Organisations, Academia, and Industry in South Africa, Switzerland, France
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practical workshops, and we recently partnered with KCL’s Spatial Biology Facility , an advanced centre equipped for high-resolution spatial transcriptomics and multiplex imaging, to turn large-scale data
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Medicine Hub for Applied Bioinformatics). We are looking for an ambitious candidate with established expertise in bioinformatics, specifically dealing with large data sets and data integration. Knowledge
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modelling, CFD mesh generation in complex 3D geometries. Proficient in handling large data sets and the ability to analysis and interpret results. Experience in commercial CFD package such as ANSYS package
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: Erlangen Programme for AI” This is a 5-year programme supported by the EPSRC and is a collaboration of mathematicians and computer scientists at the University of Southampton, the University of Oxford (lead
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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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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