44 structural-engineering-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Dip" PhD scholarships at University of Exeter in United Kingdom
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, modeling and Remote-sensing to Transform carbon budgets, CLARiTy’ (https://www.schmidtsciences.org/vicc/) will reduce the persistently high land flux uncertainties in GCB by an order of magnitude. To achieve
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investment, helping to create an energetic and vibrant academic community for our students and staff. To find out more about the Department of Engineering please click on the following link: https
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PhD Studentship: Distributed and Lightweight Large Language Models for Aerial 6G Spectrum Management
-latency, and scalable operation in aerial 6G networks. In this regard, Large Language Models (LLMs) have recently emerged as a key technology to achieve adaptive 6G spectrum management. The core idea of LLM
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to search optimised model structures, complementing RL’s incremental updates. Consideration of robustness to various sources would be an objective too. Expected Contributions A novel framework combining
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Science and Services (TESS) lab (https://tess-lab.org/ ) in the Department of Geography, Streatham Campus, Exeter. Funded by the Saudi NEOM project, eligible students would receive Home tuition fees, a
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, modeling and Remote-sensing to Transform carbon budgets, CLARiTy’ (https://www.schmidtsciences.org/vicc/) will reduce the persistently high land flux uncertainties in GCB by an order of magnitude. To achieve
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addition, data augmentation methods to improve generalisation will be explored, for example through structured transformations such as permuting satellite IDs to enforce homogeneity. The project may also
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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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Topography. Examples of post-storm relevant spaceborne missions include, BIOMASS L-band Synthetic Aperture Radar (SAR), NISAR SAR, and GEDI LiDAR, that can capture structural information about the forests
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to search optimised model structures, complementing RL’s incremental updates. Consideration of robustness to various sources would be an objective too. Expected Contributions A novel framework combining