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beaver wetlands into management and policy. Using a suite of approaches including hydrological and hydraulic models, flume experiments geospatial analysis and field validation this PhD will seek to gain
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into rivers to restore natural processes, are increasingly employed to address habitat degradation, biodiversity loss, and flood-risk. This PhD aims to monitor and model the ecological responses of plant and
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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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deliver this service, and on what scale? This PhD project will provide the tools to answer that question. Building on data and findings from the UK’s CONVEX seascape survey, this studentship will
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stability and safeguarding food security. Recent evidence points to the microbiome as a key determinant of host health and stress tolerance, but its role in bivalve resilience remains poorly defined. This PhD
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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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The University of Exeter’s Department of Engineering is inviting applications for a PhD studentship co-funded by the partner Hydro International and University of Exeter Faculty of Environment
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are urgently needed to monitor PFAS in water and probe their interactions with biological systems. This PhD project will develop a cutting-edge single-molecule optical sensor for real-time, ultra-sensitive PFAS
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an integrated, web-accessible health database for the population. The student will draw on a wide range of health-relevant data – including body condition, fecal hormone concentrations, and detailed behavioural
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an important role in the efficient integration and management of solar energy in modern power systems. The studentship project aims to develop a novel PV forecasting model based on physics-informed neural