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and enthusiastic researcher to develop their career in statistical epidemiology within the internationally leading Department of Statistics in the University of Oxford at a critical time for this field
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and enthusiastic researcher to develop their career in statistical epidemiology within the internationally leading Department of Statistics in the University of Oxford at a critical time for this field
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of Alcohol Research and the Liverpool University Hospital Foundation NHS Trust. You will have expertise in health data, data science, statistical modelling and/ or artificial intelligence. You will be based in
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, statistics or relevant subject area such as molecular biology. You should have strong computational skills and have past experience working with RNA and small compound data sets. Critical thinking, good
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Therapeutics in collaboration with the Liverpool Centre of Alcohol Research and the Liverpool University Hospital Foundation NHS Trust. You will have expertise in health data, data science, statistical modelling
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, with staff drawn variously from economics, sociology, social policy, demography, psychology, anthropology and social statistics. We promote problem-solving interdisciplinary research on particular themes
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-based proteomics experiments. Data analysis of various kinds of proteomics experiments including statistical analysis and data visualization, Development of sample preparation and LC-MS methods for low
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composites. They will also have prior experience in experimental statistical design, in vitro cytotoxicity and functional osteogenic cell testing. Prior knowledge of the fields of bone tissue augmentation and
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solutions. MA/MSc or above in AI, Natural Language Processing, machine learning, computer science, statistics or data science. What you will receive in return 32 days annual leave plus statutory public
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, psychology, sociology, epidemiology or statistics) along with experience in planning and developing independent, original, significant and rigorous contributions to your subject area and publishing empirical