13 parallel-computing-numerical-methods-"Simons-Foundation" positions at The University of Edinburgh
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computer vision method for medical image analysis principally in oncology or pathology, with a possible focus on generative AI, explainability, multi-modality. Candidate’s profile A good Bachelors degree
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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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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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to the controls (Mason et al., 2023 Communications Biology). In this project, we aim to further optimise our OCE imaging platform and apply new methods (e.g. Quantitative Phase Imaging (QPI)) to expand
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compatibility with traditional composite matrices. Explore complementary computational fluid dynamics-discrete element method (CFD-DEM) simulations as a tool to predict fibre-fluid interactions and inform