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the solution of governing PDEs. - Train machine learning models to predict lifetime and failure based on loading and environmental histories. The PhD student will have access to world-class computing facilities
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investigating the neural and computational basis of anergia and effort hypersensitivity in depression. You will be responsible for: conducting behavioural, ambulatory smartphone-based and neuroimaging assessments
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networking with colleagues and students; planning and organising research resources and workshops. Successful applicants will have or be near to completing a PhD in computer science, information engineering
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multispectral and/or SAR data to improve biomass recovery estimations, measuring biases between GEDI and EO time-series estimations, developing customised hybrid neural networks (e.g., CNN-LSTM for capturing both
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We are inviting applications for a fully funded 3.5-year PhD Computer Science studentship at the University of Warwick, jointly supported by GlaxoSmithKline (GSK), to work on an ambitious project
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The University of Exeter’s Department of Psychology is inviting applications for a PhD studentship funded by GABA Labs and University of Exeter to commence on 22 September 2025 or as soon as
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PhD programme within QMUL’s Wolfson Institute of Public Health, under the supervision of Dr Giuliano Russo (WIPH) and Prof. Pietro Panzarasa (School of Business and Management). As part of the project
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This self-funded PhD research project aims to advance the emerging research topics on physics-informed machine learning techniques with the targeted application on predictive maintenance (PdM
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technologies, neurodegeneration models, and interdisciplinary collaboration. This is an exciting opportunity to contribute to a growing research programme with the potential to lead to PhD study or further
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to machine learning and deep neural networks, into the DG finite element solver to reduce computational costs while maintaining the accuracy. The key objective of this work will be to provide step-change