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exciting opportunity to lead innovative research at the interface of AI and clinical medicine, working within a 40-strong interdisciplinary team spanning AI, statistics, microbiology, epidemiology, public
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relevant subject area, like Economics, Statistics, Maths, or other quantitative social sciences. Additionally, they must possess, or expect to receive a Master’s-level qualification, or equivalent, with
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Statistical experience (as acquired through class or a research project) [For Latin America project only] Spoken and written Spanish (CEFR B2 level or above) Desirable characteristics: Existing insight
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filled. This fully funded PhD explores AI-native and sensing-aware wireless systems where communications and sensing are co-designed end-to-end. You will unify modern machine learning, statistical signal
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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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of these three key areas: quantitative user studies, statistical modelling of human experimental data or human augmentation very good in scientific writing and communication skills very good knowledge
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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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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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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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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