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project will enable you to further your mathematical understanding with real-world applications and real-world impact. The successful applicant will split their time between the Department of Statistics and
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class Bachelor’s degree, or a Master’s degree with merit or distinction, in Mathematics, Statistics, Computer Science, or a related quantitative discipline. International qualifications of an equivalent
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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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suitable to candidates with a wide range of backgrounds such as but are not limited to: climate science, psychology, mathematics, geography, environmental science, law, computer science, public health
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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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Kevin Wilson, School of Mathematics, Statistics & Physics Dr Holly Fisher, Population Health Sciences Institute Eligibility Criteria You must have, or expect to achieve, at least a 2:1 Honours degree
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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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Master’s degree (or other equivalent experience). Suitable backgrounds for these PhD positions include, but are not limited to, power engineering, industrial engineering and operations research, mathematics
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study visa before admission. Eligibility Applicants must hold, or expect to hold, at least a UK upper second-class degree (or non-UK equivalent qualification) in Mathematics, Statistics, Physics, Computer