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artificial intelligence methodologies. The successful candidate will work at the forefront of computational biology, developing novel approaches for large-scale genomic data analysis and contributing
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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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techniques to enable large-scale data search across Personal Online Datastores (pods) hosted on distributed pod servers, addressing both keyword-based search and SPARQL querying. EPRESSO will build on and
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University to focus on data collection in the North East. The two research fellows will work closely together. You will have a PhD (or near to competion) in Nutritional Epidemiology or a closely allied
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will be applied upon successful completion of the PhD. Prior to the qualification being awarded the title of Senior Research Assistant will be given. You will join a large and friendly Mechanical
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following skills and experience: Essential criteria PhD qualified in relevant subject area Experience working with large datasets e.g. CPRD or similar Experience with relevant statistical software (STATA or R
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tenable for up to 4-years. Applications are welcome from graduates of any university. Candidates will usually have completed their PhD, but must not have undertaken more than 3-years of postdoctoral work by
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for Research Staff Development for more information. About You To be successful in this role, we are looking for candidates to have the following skills and experience: Essential criteria PhD qualified in
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Implement and test different ML architectures for postprocessing precipitation forecasts over India. Determine how to maximise information extracted from the raw forecasts and how to optimise postprocessing
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About us Our Big Data in Health team at the University of Southampton is based in the Primary Care Research Centre. We are an interdisciplinary group conducting innovative research to address