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scattering with computer modelling such as molecular dynamics simulations and AI-assisted data mining. The new technical capabilities will help bridge the current gap in biocide development, i.e., to link
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develop AI- and deep learning–based computer vision tools to automatically identify and quantify intertidal organisms. Beyond computer vision, it will leverage machine learning for large-scale, data-driven
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for Postdoctoral Researchers/Research Fellows in the following areas: Areas of interest: Privacy and Compliance, User Experience; Computational Data Science and Applications; High-performance, Energy-efficient
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aims to quantify how the superficial geology, bedrock aquifers and mine systems of Gateshead and Newcastle influences groundwater flood risk and water contamination. For further information
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Conventional metal mining, in which minerals are physically extracted from the subsurface and then processed to recover target metals (which often make up only a small fraction of the total mass) is
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most exploited natural resource after water, and riverbed sand mining has increased dramatically in recent decades. This activity reshapes river channels, altering their topography, destabilising banks
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voting platforms to public consultation tools, these platforms must not only serve communities effectively but also withstand rapidly evolving security threats. The impending transition to a post-quantum
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rate). Additional project costs will also be provided. Overview The North East has a proud coal mining heritage, with hundreds of abandoned and flooded mine seams. Current groundwater levels
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evolve under and after mining. These observations will be complemented by physical experiments in the Ven Te Chow Hydrosystems Laboratory at UIUC, using 3D-printed riverbed models derived from field data
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Fixed-term: The funds for this post are available for 3 years. A doctoral studentship is available in the forthcoming Aspirational Computing Lab (February 2026) in the Department of Computer Science