28 big-data-and-machine-learning-phd Fellowship positions at University of London in Uk
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exciting project that will develop new approaches to handle missing data in statistical analyses based on machine learning methods. The Research Fellow will be based in the Department of Medical Statistics
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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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relevant PhD and medical degree alongside registration with the GMC at Specialist Registrar Garde or below. You will have a recent track record in histopathology and use of machine learning techniques, and
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postgraduate student learning through their specialty discipline. We are looking for candidates with an RCVS registrable degree in veterinary science, who also hold or are eligible to sit an American or European
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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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large health datasets on topics including pharmacoepidemiology and non-communicable diseases. The post requires strong data management and quantitative skills with expertise in a common statistical
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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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to important public health topics. Studies will include descriptive epidemiology and use emulated target trial approaches for robust causal inference within large national health datasets. The post offers
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environmental epidemiology research team at LSHTM to work on a new UKRI-funded study in the field of climate change and health entitled THERM-UK. This is an exciting opportunity to be part of a large
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to achieve a higher degree during the fellowship (e.g. PhD) and will need to have excellent academic and organizational skills, ideally with previous experience of data analysis and/or genetics. About the