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Computing Applications and Research (CHEDDAR), we are focused on advancing the integration of UK expertise in communications and networking to maintain the country's leadership in 6G technologies. Our
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units in neural networks, which drive both artificial and natural intelligence. Current projects span a wide range of topics in deep learning theory and theoretical neuroscience. For more information and
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systems, with emphasis on criteria for robustness, reliability, and stability. Topics of interest include the study of symmetries and equivariance and their implementation in deep neural networks
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academia. Establish sustainable feedback mechanisms and support networks that will continue beyond the life of the project. Lead on project communications, including social media engagement, information
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modelling, CFD mesh generation in complex 3D geometries. Proficient in handling large data sets and the ability to analysis and interpret results. Experience in commercial CFD package such as ANSYS package
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engineering, artificial intelligence, advanced communications and cybersecurity capabilities for future urban mobility applications. We aim to develop innovative solutions that can be commercialized
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engineering, artificial intelligence, advanced communications and cybersecurity capabilities for future urban mobility applications. We aim to develop innovative solutions that can be commercialized
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systems, with emphasis on criteria for robustness, reliability, and stability. Topics of interest include the study of symmetries and equivariance and their implementation in deep neural networks
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. The project, "Building the bridge from GWAS to Breeder through multi-omic network data fusion", focuses on transforming GWAS discoveries into actionable breeding insights. Using sorghum as a model, the work
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Belfast) who have a history of policy-relevant research in the area of youth crime and crime prevention, as well as a community partner (Centre for Effective Services) with expertise in implementation