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advanced nanoengineering techniques, the project seeks to achieve a DA biosensor with superior sensitivity, selectivity, and stability, optimised for use in complex biological environments. Background
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to understand the drivers and dynamics of sediment transport along this highly populated and vulnerable river. Additionally, it will explore the use of prototype water quality sensors (Hydrobeans) to understand
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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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storm to use these technologies and/or visit the affected area to evaluate storm-related tree damage. Therefore, to support sales planning and the safety of foresters working in the field, there is a need
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-making process. Research Objectives Model Learning in Dynamic Contexts Investigate the use of reinforcement learning for constructing and updating probabilistic world models (transition and observation
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-making process. Research Objectives Model Learning in Dynamic Contexts Investigate the use of reinforcement learning for constructing and updating probabilistic world models (transition and observation
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health status, the project will identify host–microbe interactions that enhance or constrain resilience. Research will use UK coastal environmental gradients and laboratory experiments to disentangle
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) who will offer site access, data sharing, methodological guidance, and pathways for embedding results within restoration practice. Collaborative Partner Natural England will provide access to site
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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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of their student visa, healthcare surcharge and other costs of moving to the UK to do a PhD .