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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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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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quantitative connections between the continuum parameters and the underlying microscopic mechanics. Numerical study. Implement the models in computational codes to design and optimize morphing strategies. During
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characterisation methods. Subject to student eligibility and availability of opportunities, they will be able to teach, engage in public outreach or explore other opportunities complementary to their research
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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 computational approaches to analyse and integrate single-cell and spatial multiomic datasets to unravel the effects of nucleic acid-sensing pathways (e.g. cGAS/STING, RIG-I, MDA5 and others
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funded through the EU Research Framework Programme? Horizon Europe - MSCA Marie Curie Grant Agreement Number 101226708 Is the Job related to staff position within a Research Infrastructure? No Offer
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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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out numerical modelling for molecular dynamics simulation, will have experience in laser processing or other shockwave processing techniques, and will have a sound understanding of solid-state chemistry
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computing. Current challenges in quantum technology adoption stem from the lack of standardized benchmarking methods and the inherent difficulty in validating quantum devices beyond classical simulation