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to the analysis of time series. In particular, the project will examine and develop methods that go beyond the Markovian paradigm. It will consider a range of time series data, focusing on those that show
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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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individually, make a real difference. The role We are looking for a part-time research assistant (1 day a week for a year) to work with us on a project that aims to develop a set of resources that support
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individually, make a real difference. The role We are looking for a part-time research assistant (1 day a week for a year) to work with us on a project that aims to develop a set of resources that support
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: Diagnosis, RehabilitatiOn & Prognosis). The Doctoral Researcher (DR) will join a cohort of DRs who will be working on a series of interlinked, interdisciplinary projects for sustainable, intelligent, and
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. This project will investigate how such oscillations can be mitigated using series connected flexible AC transmission (FACTS) devices. The project will be carried out in close collaboration with GE Vernova
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: Diagnosis, RehabilitatiOn & Prognosis). The Doctoral Researcher (DR) will join a cohort of DRs who will be working on a series of interlinked, interdisciplinary projects for sustainable, intelligent, and
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such as landslide movement style, runout, and how landslide hazards evolve over time. This Ph.D. project will leverage the analysis of new time-series data from cloud-based satellite image archives
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nature-based solution opposed to traditional ‘grey’ engineering, offer catchment-level solutions by using natural processes to slow and store water through a series of diffused interventions. Historically
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to air pollution in the future, and planning further policy changes. This PhD project will develop statistical modelling frameworks that are able to handle large-scale, complex, and correlated time series