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<span lang="en"> Helmholtz-Zentrum Hereon</span> | Geesthacht, Schleswig-Holstein | Germany | about 13 hours ago
, phase-field modeling, precipitation modeling, and machine learning approaches to establish quantitative composition-process-structure-property relationships. Building upon recently developed machine
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system modeling Basic understanding of graph neural networks, foundation models, data-driven modeling, or physics-informed machine learning Good programming skills in Python Experience with machine
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PhD student in generative modeling for data-efficient machine learning Norrkoping Reference number LiU-2026-02831 We are now looking for a PhD student in machine learning with a focus on generative
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and modeling of electronic and optical devices Develop hardware-aware machine learning models incorporating electronic and optical device constraints Design and implement hardware-efficient training
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Instructions Application through http://jobbnorge.no : https://www.jobbnorge.no/en/available-jobs/job/302170/up-to-5-phd-fellows-in-machine-learning-at-the-arctic-institute-for-ai-in-science-and-innovation
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, and collaborate closely with Prof. Miguel Caro's group, whose core expertise is the development of machine-learning-infused atomistic modeling techniques and their application to important problems
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and clinical datasets Statistical modeling and survival analysis Machine learning and retrieval-augmented AI models for biomarker prioritization and decision support ·Work closely with cross-functional
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and clinical datasets Statistical modeling and survival analysis Machine learning and retrieval-augmented AI models for biomarker prioritization and decision support ·Work closely with cross-functional
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methodologies including machine learning approaches, and performing coarse-graining to obtain effective models at various scales. Special Instructions Contact Information Jason Eldridge https
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 20 minutes ago
possible future measurements. Examples include: determination of high-resolution shape models using shape-from-shading or novel machine-learning methods; studies of high-resolution shape models for