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(1–4) and in related projects. We encourage potential PhD candidates to visit our webpage to learn more about the research we are conducting. The PhD candidate is expected to be enrolled in two
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learning. This PhD provides a unique opportunity to shape emerging concepts in Artificial Intelligence Informed Mechanics (AIIM), combining fundamental research with methodological innovation. You will gain
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analysis. • Hydrological and hydraulic simulation. • Machine learning, including unsupervised clustering and predictive modelling. • Working with large, complex, multi-source datasets using MATLAB, Python
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both independently and as part of an international, interdisciplinary team Assets•Experience with computer vision or deep learning (e.g. PyTorch, TensorFlow)•Familiarity with street view imagery or other
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SFI FAST: PhD position in Microstructure/texture evolution during extrusion of scrap-based Aluminium
that you are particularly suitable for a PhD education. You must meet the requirements for admission to the faculty's doctoral program (https://www.ntnu.edu/nv/phd) PLEASE NOTE: For detailed information
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Exciting and high-profile interdisciplinary research on visualisation, machine learning, and human-computer interaction Comprehensive computer infrastructure for AI and the analysis of large data volumes A
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/ ) at the Department of Clinical Microbiology, at Umeå University (https:// www.umu.se/en/department-of-clinical-microbiology/ ), the PhD candidate work in the Marie Skłodowska-Curie (MSCA) Doctoral Network GLYCOCALYX
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20 Feb 2026 Job Information Organisation/Company Centrale Supelec Department L2S Research Field Engineering » Communication engineering Researcher Profile First Stage Researcher (R1) Positions PhD
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, network science, and decentralized machine learning. Welcome to read more about us at: https://liu.se/en/organisation/liu/isy/ks . For more information about working at ISY, please visit: https://liu.se/en
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CIIMAR - Interdisciplinary Center of Marine and Environmental Research - Uporto | Portugal | 16 days ago
highly motivated and oriented towards research in computational biology applied to microbial genomics and natural products biosynthesis. Experience in machine learning and the application of artificial