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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
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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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. This can impair performance and result in injury or illness. Therefore, identification of optimal recovery strategies to alleviate post-exercise muscle damage and soreness is crucial. Post-exercise nutrition
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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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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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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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the power of AI/ML and software-defined networking (SDN), and distributed learning methodologies, the research will focus on creating self-configuring, self-optimizing, and self-healing mechanisms for real
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mapping using a team of highly mobile legged or legged-wheeled robotic platforms. The research will investigate advanced algorithms for multi-robot coordination, dynamic path optimization, and collaborative
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-specific mutations in stem cells Differentiating these cells into insulin-producing beta cells Exploring genomics, cell biology, and molecular techniques to understand and optimize beta cell development
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multiple objectives in real-time. The complexity of coordinating these distributed systems while ensuring stability and optimal performance presents a significant technical barrier that must be overcome