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Application’. Use ‘Course Search’ to identify your programme of study: · search for the ‘Course Title’ using the programme code: 8040F · select ‘PhD Civil Engineering – Water Resources (full time
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, decision-making devices. Operating at the edge imposes strict constraints, including limited compute and memory resources, intermittent connectivity, strong privacy requirements, and tight energy budgets
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and architectures that support efficient, secure, and scalable machine learning operations (MLOps) across resource-constrained environments for Edge AI. Ethical, and responsible FL for healthcare: In
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sacrificing physical realism. The goal is to improve uncertainty quantification, risk reduction and assessment of low-carbon geothermal resources, supporting sustainable energy innovation. This project
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attention to boundary conditions and heterogeneity. The outcomes will support improved design, risk reduction and development of low-carbon geothermal resources. This project addresses sustainable resource
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resources in North and East England, using a combination of physically-based hydrological modelling tools and water system models. The framework will be used to produce more transparent and physically
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addressing sustainable resource extraction for geothermal heating. The outcomes will support improved prediction, design, and performance assessment of geothermal systems, contributing to risk reduction and
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hydrological systems. This project will develop a robust modelling framework to simulate future changes in water resources in North and East England, using a combination of physically-based hydrological
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of water insecurity in Mexico City, with the goal of identifying sustainable, equitable, and long-term strategies for resilient water resource management. The research will explore three core dimensions
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for resilient water resource management. The research will explore three core dimensions: transboundary water dynamics, institutional and policy effectiveness, and the impacts of climate variability on urban