39 assistant-professor-and-human-computer-interaction PhD positions at University of Exeter
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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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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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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 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
is to exploit transformer-based attention mechanisms to model sequential dependencies and capture long-range interactions, making them promising tools for complex spectrum management. Despite being
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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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the programme please see http://nercgw4plus.ac.uk/ For eligible successful applicants, the studentships comprises: An stipend for 3.5 years (currently £20,780 p.a. for 2026/27) in line with UK Research
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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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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