40 web-programmer-developer-"https:" "UCL" PhD positions at University of Exeter in United Kingdom
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to train tomorrow’s leaders in earth and environmental science. For further details about the programme please see http://nercgw4plus.ac.uk/ For eligible successful applicants, the studentships comprises
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enquiries to: Johan Wahlstrom (j.wahlstrom@exeter.ac.uk) Please ensure you read the entry requirements for the potential programme you are applying for. To Apply for this project please click on the following
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person. Aims: The project aims to develop and evaluate AI methods for medical image analysis to detect diabetic retinopathy, glaucoma, cataract and age-related macular degeneration (AMD). As
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behaviour in a practical, real-time monitoring system requires advances in both sensor engineering and behavioural data interpretation. This PhD project aims to develop a next generation environmental
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to address urgent challenges in animal conservation and welfare. However, existing technologies have mostly been developed for use in controlled laboratory settings and are often unsuitable for field
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. The framework consists of three key technical innovations. First, a multimodal encoder will be developed to project heterogeneous network data (e.g., time-series, sequences, graphs) into a token-like embedding
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equitable access to clean energy. By linking technical innovation with legal reform and social inclusion, this project aims to develop a regionally tailored strategy for sustainable, just energy transition
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This project is a fully funded MSc by Research Scholarship in Medicinal Chemistry / Synthetic Organic Chemistry and builds on a successful decade-long research programme at the University of Exeter
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, Science and Economy, to commence on 1 January 2026 or as soon as possible thereafter. This PhD project aims to develop advanced, climate change resilient road gully grating designs that enhance efficiency
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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