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the central challenge hindering this vision: the fundamental incompatibility between text-native LLMs and the operational reality of computer networks. Directly applying LLMs is impeded by three core technical
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PhD Studentship: Distributed and Lightweight Large Language Models for Aerial 6G Spectrum Management
such a promising technology, the centralised and resource-intensive nature of current LLMs conflicts with the constraints of aerial 6G networks in terms of limited computation, energy, and communication
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decision-making. Examples include crowd management and large-scale communication networks based on cellular or wireless sensors. For instance, during mass gatherings such as the sport matches (e.g
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impacts and suboptimal decision-making. Examples include crowd management and large-scale communication networks based on cellular or wireless sensors. For instance, during mass gatherings such as the sport
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to quickly quantify the damage to forest plantations after a cyclone or a tropical storm. There is unrealised potential in using multi-modal computer vision methods that synthesis multi-source Earth
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mortalities, economic loss, and human health risks through contaminated seafood. A low-cost, deployable sensor network based on mussels could provide real-time environmental intelligence, supporting regulatory
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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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networks, which could be used to support the transition to a sustainable, low-carbon energy future. The studentship will be awarded on the basis of merit. Students who pay international tuition fees
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, durability, and environmental sustainability, while addressing cost constraints and net zero objectives. It will include an in-depth review of shortcomings in current design, based on literature review and