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environments like health care and environmental monitoring. This PhD project aims to address these challenges by exploring how evolutionary algorithms and reinforcement learning (RL) techniques can be combined
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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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About the Partnership This project is one of a number that are in competition for funding from the NERC Great Western Four+ Doctoral Training Partnership (GW4+ DTP). The GW4+ DTP consists of the Great Western Four alliance of the University of Bath, University of Bristol, Cardiff University and...
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About the Project Project details The forestry industry in New Zealand, with NZ$5.89 billion in annual export revenue, is under pressure due to cyclones and tropical storms. Sales are arranged ahead of harvest using estimates of wood production constrained by UAV and Airborne laser scanning...
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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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relentless arms race. While viruses evolve new infection strategies, archaea evolve new antiviral defence mechanisms. However, we still lack a clear picture of this process. This project will address
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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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future climate change affect these hazards? The PhD researcher will have scope to determine: Selection of study rivers/locations; hazard focus (river migration by bank erosion or avulsion); methodological
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, where the default token-by-token prediction mechanism is slow and prone to "hallucinating" physically invalid configurations; and the prohibitive adaptation costs of fine-tuning billion-parameter models
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environments like health care and environmental monitoring. This PhD project aims to address these challenges by exploring how evolutionary algorithms and reinforcement learning (RL) techniques can be combined