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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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here: Demonstration of Deterministic QC with one clean qubit (DQC1) on a neutral atom array How to apply If you would like to apply then please read the guidance on applying for a PhD studentship here
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and deterministic AI outputs is critical. This requires robust design principles and architectural changes to reduce variability and integrate smoothly with industrial control systems. Enhancing
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. A non-deterministic AI machine learning model for the identical task would not offer this demonstrability or, critically, the repeatability of classical algorithm-based systems. Furthermore, there is
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skills are key. You will be working alongside the team to analyse existing case studies, organise and run a series of interdisciplinary round tables, develop a set of resources and write reports. You will
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skills are key. You will be working alongside the team to analyse existing case studies, organise and run a series of interdisciplinary round tables, develop a set of resources and write reports. You will
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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