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About the ProjectProject details Self-adaptive and autonomous systems are increasingly deployed in dynamic and uncertain environments, where effective decision-making relies on accurate models
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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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The University of Exeter has a number of fully funded EPSRC (Engineering and Physical Sciences Research Council ) Doctoral Landscape Award (EPSRC DLA) studentships for 2026/27 entry. Students will be given sector-leading training and development with outstanding facilities and resources. The...
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relies on accurate models of how the system interacts with its environment. Traditionally, such world models—comprising transition and observation models—are specified by domain experts, based
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About the ProjectProject details: Next-generation networks are rapidly outscaling the capabilities of traditional management paradigms. While early AI/ML models offered a degree of automation, they
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to other indicators of unrest, such as seismicity. This PhD project will drive innovation in modelling magma-mush processes and the generated surface deformation and seismicity during unrest episodes
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climate models, including the UK Earth System Model (UKESM), resulting in critical gaps in both seasonal forecasts and long-term climate projections. This PhD will develop a new parameterisation of snow
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will develop and evaluate new approaches to predicting current and future population exposure to such hazards by combining numerical modelling and remote sensing of river migration, with machine learning
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. CASE Partner Met Office has developed the JULES model that will be used by the PhD student to explore the role of charcoal in soil carbon dynamics. Through various discussions, Met Office staff have
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of pseudorange correction models. Enforcing such constraints offers substantial potential benefits, including faster convergence, improved generalisation, and reduced overfitting. At the same time, these benefits