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-month position is funded by the Engineering and Physical Sciences Research Council (EPSRC) as part of the pioneering project "Vascular Computational Modelling in Chronic Kidney Disease (VASCO-CKD
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of Mathematics, Informatics and Statistics, Ludwig-Maximilians-Universität München, using the following link https://www.efv.verwaltung.uni-muenchen.de/md3 no later than 7st October 2026, and also sent in
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) Application Deadline 10 Nov 2026 - 00:00 (UTC) Country Macao Type of Contract Permanent Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the
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) Application Deadline 10 Nov 2026 - 00:00 (UTC) Country Macao Type of Contract Permanent Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the
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responses; (iii) systematic evaluation of the trustworthiness of developed models through dedicated benchmarks and evaluation protocols Where to apply Website https://www.unimore.it/it Requirements Additional
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of coronary artery disease and supporting clinical decision-making during catheterization procedures. The project brings together cardiovascular imaging, generative AI, and computational modeling to develop
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provide faculty-level scientific continuity, lead experimental strategy, coordinate studies across collaborators and core facilities, troubleshoot complex leukemia models, interpret integrated datasets, and
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experience-dependent plasticity. Our research combines structural and functional neuroimaging, EEG/MEG, behavioural methods, computational modelling, automated neuroanatomical phenotyping, machine learning and
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, survey sampling, survival analysis, epidemiological methods, mixed, hierarchical or latent variable models, or multivariate analysis. Courses in computer science, especially those focusing on programming
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satisfactory performance and the availability of funding. The successful candidate will work with Dr. Yulong Lu on research projects related to the mathematical and computational foundations of generative