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For informal enquiries please contact: Professor Karen West, karen.west@bristol.ac.uk How to apply: Please consult our research proposal guidance then submit an online application for this project at http
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Networks. Knowledge of and experience in Python, TensorFlow, Keras, or other Machine Learning toolboxes, is essential. Knowledge of and experience in Large Language Models is highly relevant. The successful
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, water quality and meteorological datasets routinely collected by water utilities. The student will have the opportunity of using state-of-the-art machine learning methods (predictive analytics) to analyse
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, neuroscientists and clinicians in a highly interdisciplinary environment. You will apply computational and machine learning approaches to control theory problems, implement real-time digital signal processing
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hydro-climatic conditions govern vegetation behaviour, and how vegetation impairs the functioning of drainage and water-management assets. Using advanced geospatial modelling, machine learning and digital
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Application deadline: 30/04/2026 Research theme: Nuclear Engineering How to apply: https://uom.link/pgr-apply-2425 This 3.5-year PhD project is fully funded; home students are eligible to apply
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of WAAMMat (https://waammat.com/ ), gaining valuable industry experience and exposure. The student is expected to acquire the following (including but not limited to) knowledge and skills from the research in
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during domestic abuse responses? Qualitative interviews with police officers will be conducted. This project is delivered in partnership with Operation Encompass (https://www.operationencompass.org/ ), a
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We are recruiting a new fully-funded PhD student to join Dr Daniel Yon’s Uncertainty Lab at the School of Psychological Sciences at Birkbeck, University of London. This post is attached to a recent grant awarded to Dr Yon from the Leverhulme Trust entitled Public Communication and Private...
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. During the PhD programme, a student would be expected to explore the design of advanced computer networks, both through simulation and the direct execution of workloads on real-world implementations. As