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into practical performance solutions. The “Travel, sleep and fatigue optimal management for long-haul performance” PhD programme will focus on mitigating circadian and travel fatigue challenges associated with
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bridging the gap between computational intelligence and structural engineering, this research aims to develop a self-adaptive monitoring and optimization system for CFDST wind turbine towers, enhancing
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machine structures, together with AI-driven optimization frameworks for diverse applications while considering LCA metrics. The success of this project could serve as a model for other energy-related
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its environment and respond optimally in dynamic operating conditions. Meanwhile, you will also develop intelligent control strategies that minimise energy use while ensuring punctuality and safety
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2:1 undergraduate honours degree in a relevant subject and meet our English language requirements. They should have a strong background in physics and/or mathematics (e.g., PDE, optimization) and/or
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optimise a ‘Digital Twin’ of the Tees estuary to ensure that the NBS are deployed at locations optimal for performance and longevity while operating within the constraints placed upon deployment by other
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seek optimal trade-offs between compactness and performance, delivering foundational insights into the future of high-performance electric propulsion systems. Funding 3-year PhD tuition fee (for UK home
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drive the gradual development of these technologies toward real-world applications. This involves engineering experimental hardware for cell culturing workflows, optimizing experimental processes, and
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alloys), and additive manufacturing to push performance boundaries. The research will seek optimal trade-offs between compactness and performance, delivering foundational insights into the future of high
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and embrittlement by precisely optimizing additive manufacturing parameters. By combining experimental investigations, advanced microstructural analyses, and numerical simulations, a novel manufacturing