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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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(e.g. 2.1 or above undergraduate degree in physics, mathematics or computer science) Willingness to adapt and work across different disciplines Ability to work independently and cooperatively Commitment
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of eligible participants, clinical trials in rare diseases often cannot achieve the standard 80% or 90% power requirements, alongside a 5% type I error rate, in the final analysis. There is widespread
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Failure Analysis of Composite Sleeves for Surface Permanent Magnet Electrical Machines This exciting opportunity is based within the Power Electronics, Machines and Control (PEMC) and Composites
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, hierarchical and composable analysis and design is needed. The project will leverage tools from contract-based design theory to formalise such security and performance guarantees at multiple resolutions
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AI models more interpretable and reliable by incorporating known constraints or physical properties. The successful applicants will be part of the Prob_AI hub and the School of Mathematics
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permanent magnet electrical machines are pushing performance boundaries. A major challenge is the structural integrity of the carbon-fibre reinforced polymer (CFRP) sleeves used to contain the rotor’s magnets
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This project provides an excellent opportunity to develop state-of-the-art mathematical models and computational tools of emerging respiratory pathogens, within a world-renowned research group
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Profile: We seek someone with strong mathematical maturity in control theory, dynamical systems, or applied mathematics. Familiarity with nonlinear systems analysis, graph theory, and formal methods (e.g
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equations into AI-based models to solve fluid sensing problems in a robust and efficient manner. Your role may include developing new optimization techniques, coding new algorithms, creating new mathematical