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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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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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, scientific machine learning, and partial differential equations to create a new approach for data-driven analysis of fluid flows. The successful applicant will have experience in one or more of these subject
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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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/College research strategy. 2. Document research output including analysis and interpretation of all data, maintaining records and databases, drafting technical/progress reports and papers as appropriate. 3
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systems thinking mindset with robust mathematical frameworks to solve real world problems with our industrial collaborators at Rolls-Royce. Over the past 30 years, we have designed and introduced new
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spin-burst experiments, will complement advanced finite element analysis (FEA) in evaluating failure behaviour. Who we are looking for An enthusiastic, self-motivated, and resourceful candidate with a
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ecological theory and modelling with the analysis of publicly available data on degraded and restored ecosystems. Specifically, mathematical dynamical ecological frameworks informed from empirical data will be
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optimization techniques, coding new algorithms, creating new mathematical theory, and the analysis of large data ensembles. You will write papers for submission to academic journals, collaborate with academics
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, this project aims to develop a novel modelling and analysis approach to address the mathematical and technical challenges of the fluid-structure interaction (FSI) mechanisms globally. The successful PhD