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multivariable statistical methods. Support for skills development is provided within the Horse Microbiome Research Group and the university’s Doctoral College . Delivery of this project in collaboration with
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. Experience in working with large data sets, knowledge of statistics, and some programming expertise is essential. The project is based in ECEHH, at the University of Exeter’s Penryn Campus in Cornwall, and may
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, dynamical systems and statistical physics. The candidate will be jointly supervised by the Coventry team Dr Fei He and the Stellenbosch team Prof. Francesco Petruccione . This project will contribute
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subject relevant to the proposed PhD project (such as mathematics or statistics) is our standard entry, however we place value on prior experience, enthusiasm for research, and the ability to think and work
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filled The overarching aim of this project is to find synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application
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synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application to the analysis of time series. In particular, the project
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statistical models (for example principal component analysis) to obtain insights into relationships between physical properties of polysaccharides (composition, molecular weight charge, chain length etcetera
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analyse large datasets such as the Clinical Practice Research Datalink (CPRD) and Hospital Episode Statistics to identify activity related to the treatment of community acquired pneumonia. This will require
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teach you many translatable skills and knowledge from the fields of sleep medicine, sleep physiology, statistics, artificial intelligence, and psychology for example. A very significant and specific
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economic studies funded by the UK National Institute for Health and Care Research. Experience of conducting economic evaluations using suitable statistical software (e.g. STATA, R or SAS) is essential