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LiDAR and multispectral imageries), and lab analyses. The PhD will benefit from participation in a wider 'large wood' project with over 12-partners (including Environment Agency, SEPA, Natural England
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large herbivores and off-road driving, using the RPI to control for climate-driven variability and incorporating data from allied ground monitoring. This should reveal landscape-scale recovery timeframes
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decision-making. Examples include crowd management and large-scale communication networks based on cellular or wireless sensors. For instance, during mass gatherings such as the sport matches (e.g
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impacts and suboptimal decision-making. Examples include crowd management and large-scale communication networks based on cellular or wireless sensors. For instance, during mass gatherings such as the sport
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for computer, lab, and fieldwork costs necessary for you to conduct your research. There is also a conference budget of £2,000 and individual Training Budget of £1,000 for specialist training Project Aims and
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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
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Methods Tropical forest soils are crucial to the global carbon cycle, yet increasing wildfire, land-use change, and climate warming may cause large carbon emissions. This PhD will investigate (1) how soil
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Partner The National Oceanography Centre (NOC) will co-develop PhD project, provide scientific expertise during supervision meeting, access to numerical data and access to research facilities and training
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PhD Studentship: Distributed and Lightweight Large Language Models for Aerial 6G Spectrum Management
generation of wireless communication (6G) to extend network coverage, supporting diverse data-intensive applications such as immersive extended reality and autonomous systems. However, aerial 6G networks will
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barriers: a large input modality gap, as network data consists of diverse, non-textual formats like time-series metrics, graphs, and scalar values; the inefficiency and unreliability of answer generation