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neuroscience and data analysis Proficiency in programming (e.g., Python, MATLAB, and similar languages) Experience with large-scale neural network simulations Experience with analysing large-scale neural
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compatibility with traditional composite matrices. Explore complementary computational fluid dynamics-discrete element method (CFD-DEM) simulations as a tool to predict fibre-fluid interactions and inform
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The overall aim of the project is to resolve the quantum trust challenge where the inherently quantum nature of these devices, being beyond classical simulation, complicates their straightforward validation
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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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MRI, echocardiography, and CT. Another promising approach is the use of cardiac digital twins—mathematical models that simulate a patient’s heart to allow the design and in silico testing of novel
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MRI, echocardiography, and CT. Another promising approach is the use of cardiac digital twins—mathematical models that simulate a patient’s heart to allow the design and in silico testing of novel
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, into simulation models used for health systems management. The research will provide practical and methodological contributions. The framework will offer healthcare decision-makers better tools for designing
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scenarios. By enabling more realistic and dynamic adversarial simulations this project will support the creation of more effective cybersecurity testing, consequently strengthening organisational resilience
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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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The overall aim of the project is to resolve the quantum trust challenge where the inherently quantum nature of these devices, being beyond classical simulation, complicates their straightforward validation