11 high-performance-quantum-computing-"https:"-"https:"-"https:"-"https:" positions at The University of Edinburgh
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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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for the following programme: https://study.ed.ac.uk/programmes/postgraduate-research/495-informatics-ipab-robotics-computer-vision-computer-graphics with a start date of 14 September 2026 (home applicants
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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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Professionals in a world-leading research centre at the University of Edinburgh, with combined clinical training and practice in association with NHS Education for Scotland (NES) and NHS Lothian. The programme
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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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-value reinforcements in their short and randomly aligned form. A key challenge to the effective reintegration of recycled carbon and glass fibres into high-performance products lies in achieving scalable
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an interdisciplinary, team-based framework built around these three objectives. We will combine microfluidics, phase-change systems, bioengineering, label-free quantitative phase imaging, and high-content imaging with
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zinc-ion cells with significantly improved performance, and developed design rules that can be applied across future grid-scale storage technologies. Training and environment You will be based in
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lives. Biomimetic membranes can be vital components of electrosynbionic or biosensing devices. For maximizing performance, we need to use sophisticated nature-inspired membranes that are folded
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for selecting high-quality oocytes and predicting embryonic/pregnancy outcome is still lacking. The aim of this project is to develop a non-invasive tool for screening and selecting oocytes with the highest