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failures before they occur, enabling proactive maintenance strategies. Anomaly Detection Mechanisms: Implement machine learning techniques to identify and classify anomalies in electronic systems, enhancing
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industrial partners, such as WAAM3D (https://waam3d.com/ ) and members of WAAMMat (https://waammat.com/ ), gaining valuable industry experience and exposure. The student is expected to acquire the following
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systems safer, more efficient, and more sustainable. The aim of this project is to design a smart cognitive navigation framework that information from various sensors and learn to make decisions on its own
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of WAAMMat (https://waammat.com/ ), gaining valuable industry experience and exposure. The student is expected to acquire the following (including but not limited to) knowledge and skills from the research in
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health monitoring, supporting studies in military aircraft systems. Engaging with these facilities allows students to acquire practical skills and technical expertise, enhancing their research capabilities
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for research into thermal management and system health monitoring, supporting studies in military aircraft systems. Engaging with these facilities allows students to acquire practical skills and technical
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Machine Learning-based diagnostics and prognostics digital twin system will be developed, aiming to provide fast and reliable predictions of the health of gas turbine engines. Non-confidential operational
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Embark on a ground-breaking PhD project harnessing the power of Myopic Mean Field Games (MFG) and Multi-Agent Reinforced Learning (MARL) to delve into the dynamic world of evolving cyber-physical
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offers a modular, cohort-based training programme with emphasis on innovation and impact, collaborative working and learning, continuous development, active engagement with partners and stakeholders and
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training programme with emphasis on innovation and impact, collaborative working and learning, continuous development, active engagement with partners and stakeholders and inclusion of student-led activities