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develop roots preferentially upslope to provide anchorage against horizontal soil sliding. Greater understanding of how root system architecture and geometry provide resistance to different combinations
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PhD studentship in Trustworthy Multimodal AI under Lightweight and Data-Efficient Architectures Award Summary 100% fees covered, and a minimum tax-free annual living allowance of £20,780 (2025/26
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pseudorange correction through multiobjective optimisation. The research will explore multiple classes of constraints that will be embedded as objectives: Internal pseudorange consistency: ensuring
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About the Project The future power grid will be a highly complex cyber-physical system, integrating multiple distributed energy resources (DERs) such as solar, wind, marine, and bioenergy alongside
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will also be provided. Overview This project will develop an adaptable Machine Learning (ML) hardware architecture to solve Artificial Intelligence (AI) classification tasks using Internet of Things (IoT
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an adaptable Machine Learning (ML) hardware architecture to solve Artificial Intelligence (AI) classification tasks using Internet of Things (IoT) sensor data. This will be a small system-on-chip designed
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—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient
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—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient
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research plan for the ARTS Doctoral programme soon after being hired. The target graduation time in doctoral studies is four years at the School of Arts, Design and Architecture. You can find more
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pathways can be combined to make MECs economically and environmentally viable at scale. Research Aims: Process Intensification & Scale-Up Design and evaluate scalable MEC architectures (cassette and