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this goal. However, the computational expense of these models limits their use for generating forecasts, constraining the spatial resolution, level of physical complexity, and number of ensemble members
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Project details: Adaptive Automated Geological Modelling for Sustainable Mining Applications Sustainable mining requires a proper assessment of the risks involved in any decision in the mining value
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strategic priorities in Digital Twins, Environmental Intelligence, and Data-Driven Engineering, using advanced computational modelling to support ecosystem resilience and sustainable management. The project’s
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pilots to real-world systems. The overarching aim is to deliver a scalable approach, pairing shared “aggregator” models with household-specific “client” models that exchange knowledge while keeping data
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this project, the student will develop skills in: the structure of weather and climate models, interrogating weather and climate models with observations from the British Antarctic Survey, computational
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technology increases the grid’s exposure to cyber-attacks, which can compromise measurement signals, disrupt control commands, or induce model or data-driven instability. This project aims to develop a robust multi
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monitoring and conservation applications, while Bristol offers advanced training in machine learning, spatiotemporal modelling and AI applications to animal behaviour. Together, they provide computational
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experience with finite element or finite difference modelling and its underlying fundamentals. The student should be able to program in MATALB or Python (MATLAB preferred as lead supervisor is more familiar
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to train tomorrow’s leaders in earth and environmental science. For further details about the programme please see http://nercgw4plus.ac.uk/ For eligible successful applicants, the studentships comprises
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to train tomorrow’s leaders in earth and environmental science. For further details about the programme please see http://nercgw4plus.ac.uk/ For eligible successful applicants, the studentships comprises