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statistical and data analysis frameworks are welcomed to be proposed or developed by the candidate as part of the project. We will apply the methodologies to a wide range of data from observations to modelling
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billions of consumer devices relying on accurate positioning daily. Improving GNSS accuracy, especially for low-cost, mass-market receivers, therefore has significant economic and societal impact. However
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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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satellite SAR, LiDAR and/or optical imagery to enable rapid, safe, and scalable assessments of damage. Candidate methods for temporal modelling and anomalies detection, which are likely to occur at affected
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-tuning only a small set of low-rank matrices for each agent role, drastically reducing GPU memory and training time while preserving the model's pre-trained knowledge. The primary outcome of this research
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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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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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shipping and changing regulation now makes the ship design problem more challenging than ever. This fully-funded PhD studentship in partnership with Mari-UK, University of Newcastle and BMT Ltd, will
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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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recombination, maintaining genetic linkage of toxin/antitoxin-like systems. As a result, these chromosomes accumulate deleterious mutations that are unaccounted for in existing gene drive models. The student will