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Field
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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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informatics, biomedical engineering, statistics, or related fields. The lab is engaged in developing novel deep learning and AI-based technologies for digital biopsies from medical images and real-world
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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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algorithms. Graph Neural Networks. The candidate is expected to hold a relevant MSc degree in Computer Science, Data Science, Physics, (Applied) Mathematics, Computational Statistics or another field
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record of scientific productivity is preferable. The successful applicant must have a Ph.D.in Computer Science, Data Science, Statistics, Mathematics, Physics, Engineering or related field at the start of
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, computing, and energy economics. The successful candidate will have an excellent understanding in one of the following fields: power system operations, power system economics, linear programming, micro
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an early warning system of dementia, to be exploited within existing healthcare pathways to trigger early intervention. Skills acquisition The studentship will provide training in data-analytics, statistics
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Cynwyd, Pennsylvania 19004, United States of America [map ] Subject Areas: Statistics Industrial Engineering Mathematics Economics Management Science & Engineering (more...) Computer Science and
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Cynwyd, Pennsylvania 19004, United States of America [map ] Subject Areas: Industrial Engineering Statistics Mathematics Economics Management Science & Engineering (more...) Computer Science and
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deep learning theory, Bayesian statistics, and generative modelling, this work will advance our understanding of both the capabilities and vulnerabilities of modern AI systems. This will have potential