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techniques lack dynamic measurement capabilities and real-time feedback for therapeutic applications. Graphene’s tuneable electronic properties, further enhanced through nanoengineering, make it an ideal
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is provided by Prof Mike Allen and SeaGen, a blue-tech company based in the South West of the UK, who will support product development and route-to-market strategies. Together, the supervisory team
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this project have direct applicability to UK commercial forestry and Net Zero ambitions due to increasing tree planting programs coupled with increased extreme weather events. Please direct project specific
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to dangerous scenarios like stampedes. Managing such environments requires robust, real-time adaptation that accounts for evolving conditions and uncertainties. More application examples include real world
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Project details: Global Navigation Satellite Systems (GNSS) support a wide range of applications, from smartphone navigation to autonomous vehicles. The global GNSS market is substantial, with
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to dangerous scenarios like stampedes. Managing such environments requires robust, real-time adaptation that accounts for evolving conditions and uncertainties. More application examples include real world
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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
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PhD Studentship: Distributed and Lightweight Large Language Models for Aerial 6G Spectrum Management
generation of wireless communication (6G) to extend network coverage, supporting diverse data-intensive applications such as immersive extended reality and autonomous systems. However, aerial 6G networks will
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and Professor Xujiong Ye with input from members of our medical image analysis labs. This will enable the assessment of ML approaches for image grading and application to grade retinopathy severity