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Field
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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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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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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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to validate computational fluid dynamics modelling to determine drag and vortex-induced vibrations on dSPCs associated with biofouling. Better understanding of the hydrodynamic consequences on dSPCs from key
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allowance of £20,780 (2025/26 UKRI rate). Additional project costs will also be provided. Overview This PhD will develop a Synovium-on-a-Chip, using 3D bioprinting, microfluidic engineering, and computational
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programming (e.g., Python, MATLAB). Energy system modelling expertise with experience in academic research Preferred Skills: Educational background in Electrical Engineering, Computer Science, Renewable Energy
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Computer Science, Mathematics, or related areas. • Strong background in at least one of the following: formal methods, SMT solving, abstract interpretation, or model checking. • Experience with verification tools
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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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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description HIV remains one of the most persistent and challenging infections
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(SONATA, EP/V028626/1) and brings together expertise in microfluidics, fluid dynamics, nanoparticle engineering, and dental microbiology. Approach and Methods: Engineer in vitro models of bacterial biofilm