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shifts, and stringent latency demands render traditional beam management ineffective. This project will design, implement, and validate an AI-native predictive beam-steering framework that combines orbital
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the intersection of ecology, machine learning, and sustainable land management, the research will combine field data collection, deep learning model development, and stakeholder co-design to support biodiversity
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sensors to deliver resilient, high-accuracy positioning. The project sits at the intersection of navigation, AI-enhanced signal and data analysis, and wireless communication systems, with applications in
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research centres. It is anticipated that the new materials’ understanding and the model generated within the project will enable a faster uptake of AM materials for rotating components and help
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. The developed new knowledge will assist performance designs, analysis, operations, and condition monitoring of sCO2 power generation systems. The project will be undertaken using the strong thermodynamic
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The rapid proliferation of AI-generated synthetic media, including deepfakes and AI-assisted phishing, presents a critical and evolving challenge to enterprise cybersecurity. These threats erode
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. The project is co-sponsored by Spirent Communications, a world leader in navigation and testing technology. Spirent will provide advanced simulation tools, expert support, and industry placements to help make
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. The project delves into areas such as hardware-based security measures, tamper detection, and the integration of explainable AI models within embedded platforms. Situated within the esteemed IVHM Centre and
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at the edge. The project explores advanced topics such as TinyML, neuromorphic design, reconfigurable logic, and autonomous fault recovery, with applications ranging from aerospace, energy, and robotics
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slow sand filters. This project suits graduates seeking careers in drinking water technology, sustainable infrastructure, and low carbon process design. Drinking water production is under mounting