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programmed in advance. If anything changes, it may fail. This project explores how to build more adaptable systems using vision-language-action (VLA ) models. These combine computer vision (to see), natural language
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systems using vision-language-action (VLA ) models. These combine computer vision (to see), natural language understanding (to interpret instructions), and action generation (to respond), enabling robots
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synergistically, similar to how systems work in nature. Experimental work will include the following indicative activities: Designing and developing CAD models of test coupons and other structures Fabrication
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Award Summary 100% fees covered, and a minimum tax-free annual living allowance of £20,780 (2025/26 UKRI rate). Additional project costs will also be provided. Overview Naturally functioning
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for a given coastline morphology and flood hazard profile to minimise inland inundation, assessed using coupled CFD and inundation modelling? - How can the optimisation process balance flood reduction
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asset records, satellite imagery) with field investigations to identify vulnerable regions and understand surface deterioration processes. You’ll gain experience in spatial analysis, fieldwork, soil and
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' model. The iterative model will explore vulnerabilities and feedback loops between hydrological processes, infrastructure, and social actors. 3. Embedded Learning: Placements with the Environment Agency
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national datasets (e.g. UK Climate Projections, Environment Agency asset records, satellite imagery) with field investigations to identify vulnerable regions and understand surface deterioration processes
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weather-related extremes, much of it by our team, however we must also consider their cyber risks. Network modelling will be used to simulate a range of different cyber and natural hazards threats
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is jointly funded by EPSRC and the Department for Transport. When transport infrastructure suffers damage or disruption from events such as natural hazards (flooding, high winds) or planned maintenance