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Deadline: Monday 15th December, 2025. Competition funded PhD Project. Supervisors: Prof David Dockrell (The University of Edinburgh), Dr Brian McHugh (The University of Edinburgh), Dr Clark Russell (The University of Edinburgh) About the Project Macrophages are key innate immune cells with...
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. Our academics undertake research across a wide range of computing fields: software engineering, data science, algorithms and theoretical computer science, cyber security, communication and information
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A fully funded four-year PhD position is available to work on the project titled “Fault-Tolerant Architectures for Superconducting Qubit Quantum Computers”. This position is a collaborative
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looking for a researcher with computational expertise, who is interested in integrating and assessing transcriptomic (single cell/nuclei, long-read), proteomic and metabolomic data derived from human
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at the University of Edinburgh. Candidates currently studying outside of China are eligible to apply, but not those who have already commenced a PhD programme of study prior to the 2025-2026 academic year. The
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methods Programming with Python/Matlab The training programme will prepare the candidate for a broad range of career paths in academia, industry, and beyond. They will also participate in outreach
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of shopping/travel discounts, access to our Employee Assistant Programme Scheme, Health and Wellbeing Support and a salary sacrifice cycle to work scheme. Please follow this link to find out more
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One fully funded, full-time PhD position to work with Alessandro Suglia in the Embodied, Situated, and Grounded Intelligence (ESGI) group at the School of Informatics, University of Edinburgh
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Electrosynbionics [1] involves the use of biological parts to create devices that generate electricity, such as biological photovoltaics and biobatteries. Electrosynbionic systems can be sustainable power sources for electronics, supporting the Green Transition. Biosensing involves detection of...
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Deadline: 30 September 2025 A fully funded 3.5 year PhD position is available to work on the project titled “Scalable benchmarking for digital quantum computers based on blind testing