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pathogen screening, you will test two long-standing hypotheses: Fluctuating selection — Does spatial and temporal variation in pathogen pressure maintain diversity in immune-related genes? Antagonistic
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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
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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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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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computational fluid dynamics and numerical modelling will be used to simulate performance under varying runoff scenarios, pollution loads and climate conditions. By developing advanced road gully designs with
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Amazonian soils; and (3) how the JULES land surface model can be improved using novel field and experimental data. The doctoral researcher will shape the project, lead field experiments in southern Amazonia
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substantial intensification of the ocean heat transport, highlighting their climatic influence. However, the dynamics of submesoscale flows, and hence their representation in climate models, have not been
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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
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regions, and may have also been observed in historical trends, but the processes driving this delay are not well understood. This project will use observations and climate model simulations to examine how
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, encompassing advanced geospatial analysis, remote sensing methods, atmospheric transport modelling, and epidemiological data integration. The researcher will also receive guidance in handling large datasets