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Field
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plausible future climate, land use changes and socioeconomic development scenarios e.g. urban planning. The outcome will provide a holistic assessment of flood risk for future strategies and climate
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Approximation. Parameterized Complexity is a vastly growing area within theoretical computer science that allows for the development of exact and approximation algorithms for computationally hard problems by
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the operational life of battery-powered devices and reducing the environmental impact of large-scale deployments. Advancements in this area support the development of sustainable technologies across various
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treatments. To date, there are few techniques that integrate AI and digital twins to improve patient outcomes. Your Role In this project, you will develop new methods that combine AI and digital twins
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). The management of search and rescue organisations of casualties with cervical spine injuries has recently developed from the goal of total immobilization to the concept of selective motion control. Vacuum
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the ranking. However, STV method becomes considerably more complex with encrypted ballots. Our goal is to develop an algorithm/protocol to count encrypted ballot using the STV method. Our first point of
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signs of cardiovascular changes, adaptively model physiological patterns, and identify predictive biomarkers of maternal health. You will develop and apply cutting-edge techniques in: Signal processing
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the evidence–base needed to understand the impact on health, to inform public policy, and to develop potential mitigation strategies. Traditionally, this information has come from ground monitoring networks
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critical steps of gastrulation and early development. Creating iPSC lines with mutations in elements of the GAG biosynthetic machinery. Applying novel GAG analytical technologies to investigate how changes
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the development of specialized hardware architectures capable of efficient, real-time processing. Embedded AI hardware architectures, including neuromorphic processors and low-power AI accelerators