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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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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
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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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in an optimal way, an issue that will be prominent in industrial, commercial and residential areas across the country. The models and solutions will be developed in a general way in order to be
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, complexity, and harsh operating conditions. This PhD research addresses two critical challenges in this domain: (1) optimizing sensor movement for inspecting large and complex equipment using robots and
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research which combined efficient optimization and sequential reliability assessment. The project is funded through an EPSRC call to accelerate research outcomes to achieve a prosperous net-zero and is
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store energy by exploiting quantum phenomena (for example, by exploiting entanglement) in order to improve the performance of the device. There are still many questions surrounding the optimal