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needs. While muscle imaging from well-characterised patients and transcriptomic technologies provide rich data, these remain under-utilised for predictive modelling. Using machine learning, this project
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the development of a low fidelity pump model that accounts for unstable and multi-phase flow behaviour through high fidelity simulations. This will be used to develop an integrated fuel system model that will
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this astonishing picometre fabrication precision. Further aims of the project include: Theoretical modelling of nanoscale effects and processes in SNAP Development of experimental methods of picometre-precise
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Research Groups at the Faculty of Engineering, which conduct cutting-edge research into electric propulsion systems, composite materials, and advanced simulation technologies. Vision We are seeking a highly
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materials, particularly in modelling and/or testing Basic understanding of finite element methods (FEM); any exposure to impact or burst mechanics is a plus Familiarity with FE simulation tools such as ANSYS
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computing. Current challenges in quantum technology adoption stem from the lack of standardized benchmarking methods and the inherent difficulty in validating quantum devices beyond classical simulation
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prostate cancer risk across diverse ethnic groups. This work aims to support more equitable risk stratification in cancer screening programmes. Using simulations based on multistate modelling framework
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undertake comprehensive literature and market surveys, develop advanced simulation models, investigate integration into HVDC transmission systems, and design/test scaled-down hardware models at the ‘Wolfson
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limitations in both measurement and modelling techniques. Current in-process measurement methods are restricted to surface-only monitoring devices (e.g., cameras and pyrometers), which fail to capture
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Degradation Faults: Simulates various degradation scenarios in unmanned aerial vehicle (UAV) fuel systems, enabling research into fault detection, isolation, and prognostics. Machine Fault Simulator