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models. Geometric Deep Learning for Structural Synthesis: Leveraging Graph Neural Networks (GNNs) and manifold learning to optimise complex geometries in medical device design and advanced manufacturing
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integrity in near surface agents), and crack initiation (discontinuity between agents), with peri-dynamic inspired interagent bonds defining the structural integrity of the material. In current research
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well governed data structures that underpin reporting, analytics and statutory returns. The team develops and supports end to end BI solutions across the Microsoft stack—including ETL, data models
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research in one of the 50 research teams in the Faculty of Physics. Successful candidates will join a structured doctoral programme offering first-class supervision, vibrant research networks, and
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of Europe.Successful candidates will join a structured doctoral programme offering first-class supervision, vibrant research networks, and opportunities to publish, teach, and engage internationally.Candidates can
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Our research aims to answer fundamental questions about how cells and organisms work at the molecular and biochemical level. We study the structures and properties of DNA, RNA and protein molecules
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. This PhD project will investigate how biofouling affects the hydrodynamic, thermal and fluid-structure interaction performance of dynamic flexible cables and develop novel engineering solutions to enhance
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and ability to work in interdisciplinary teams. Desirable: B1 Knowledge of geospatial data structures and visualisation tools. B2 Skills in user-centred design, including working with collaborative
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includes a broad range of technical disciplines: Civil, Structural & Coastal Engineering, Computer Science, Electrical & Electronic engineering & Robotics, Mathematical Sciences, Mechanical, Marine
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of Leeds has recently made a significant investment into its sporting facilities with a £5.2 million investment at our Bodington Playing Fields Site. This included the construction of the new Brownlee Centre