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real-world deployment scenarios and collaborate with global organizations to ensure practical implementation and scalability. Key Research Areas: Software engineering, AI/machine learning, IoT
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aircraft, utilized for research into thermal management and system health monitoring, supporting studies in military aircraft systems. Engaging with these facilities allows students to acquire practical
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, supporting studies in military aircraft systems. Engaging with these facilities allows students to acquire practical skills and technical expertise, enhancing their research capabilities and employability in
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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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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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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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flow of realistic car shapes and their implications on pollutant dispersion under actual road conditions. Overview The PhD student will test these two hypotheses: There is a strong effect of the vehicle
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should have a strong foundation in artificial intelligence, machine learning, and multi-agent systems, along with experience in programming, data analysis, and model development. Knowledge
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analyses for new technology areas. What will you Learn? This PhD offer a wide array of transferable skills such as project management, data analysis, problem solving, critical thinking, and effective
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this issue and we could use obtain data-driven models using machine learning algorithms such as artificial neural networks, reinforcement learning, and deep learning. A typical caveat of data-driven modelling