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This research opportunity invites self-funded PhD candidates to develop advanced deblurring techniques for retinal images using deep learning and variational methods. Retinal images often suffer
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to International candidates. How to Apply All applications should be made online via the above ‘Apply’ button. Under ‘campus’ please select *Loughborough* and select the programme ‘CDT Engineering Hydrogen Net Zero
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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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select ‘Create a Postgraduate Application’. Use ‘Course Search’ to identify your programme of study: search for the ‘Course Title’ using the programme code: 8060F select ‘ PhD Electrical and Electronic
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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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Cyber-Physical Power Systems Research area and project description: This is an exciting PhD project to be carried out in close collaboration with a UK electrical network operator and an industrial co
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at Cranfield which has a strong collaborative history with industry in the field of atmospheric icing science research. This programme provides the PhD candidate with an outstanding opportunity to work across a
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for Engineering PGRs. including sessions on paper writing, networking and career development after the PhD. The Faculty has outstanding facilities and works in partnership with leading industrial partners
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bottleneck in the screening process. This PhD project will address this through deep integration of scanning probe electrochemistry, optical microscopy and machine vision, to develop a system that can
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One fully funded, full-time PhD position to work with Prof. Mahesh Marina in the Networked Systems Research Group at the School of Informatics, University of Edinburgh. The broad aim