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predictive performance, computational efficiency, and spatial resolution through algorithm optimisation, tuning, and refined covariates. Assess trade-offs between spatial resolution and other performance
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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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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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enquiries to: Johan Wahlstrom (j.wahlstrom@exeter.ac.uk) Please ensure you read the entry requirements for the potential programme you are applying for. To Apply for this project please click on the following
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for the potential programme you are applying for.
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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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programme you are applying for. To Apply for this project please click on the following link - https://www.exeter.ac.uk/study/funding/award/?id=5733
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ensure you read the entry requirements for the potential programme you are applying for. To Apply for this project please click on the ‘Apply’ button above.
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programme you are applying for. To Apply for this project please click on the ‘Apply’ button above.
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read the entry requirements for the potential programme you are applying for. To Apply for this project please click the 'Apply' button