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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
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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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communications in smart manufacturing. We are seeking an ambitious and technically capable individual with a strong academic background in Computer Science, Computer Networking, Telecommunications, or a closely
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or infrastructure. This is what makes our daily work so meaningful and exciting. The Division of Computational Genomics and Systems Genetics is seeking from October 2025 a PhD Student in Deep Learning for Rare
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NPL, the UK’s national metrology institute, is developing a fully functioning, thoroughly characterised, local area quantum network (QLAN) linking heterogeneous nodes across its site. It will make
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Networks project. Planned research will investigate the characterization and recovery of bionanoparticles for vaccine delivery and gene therapy. Overall, 14 Doctoral Candidates will be trained at seven
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Title’ using the programme code: 8856F Leave the 'Research Area' field blank Select ‘PhD in Process Industries; Net Zero (PINZ’) as the programme of study You will then need to provide the following
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-informed data analytics tools for the predictive maintenance (PdM) strategy applications to high-value critical assets. Among others, the recently developed Physics-informed Neural Network (PINN) technique
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the UKRI rate (£19,237 for 2024/25) and tuition fees will be paid. We expect the stipend to increase each year. Modernised distribution power networks face an unprecedented challenge as thousands of power
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are part of the programme. The research is funded by the Centre of Propulsion and Thermal Engineering at Cranfield University. The work will be conducted at the Cranfield icing wind tunnel (IWT) based