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PhD Studentship: Distributed and Lightweight Large Language Models for Aerial 6G Spectrum Management
on this foundation, this project will advance distributed and lightweight LLM architectures to enable resource-efficient spectrum allocation across highly dynamic and interference-prone 6G aerial environments. As LLM
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how best to balance competing objectives. We will also investigate architectural design strategies that implicitly encourage constraint adherence, such as averaging features across satellites. In
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improved hydraulic performance and pollution capture and reduced blockage risk, the research will enhance the efficiency of urban drainage systems and help mitigate flooding and pollution impacts
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