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Position Description An Associate in Research position is available in the Interpretable Machine Learning Lab ( https://users.cs.duke.edu/~cynthia/home.html ) for a scientific developer to work in
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, and physics-informed machine learning open new possibilities for establishing grid foundation models. However, it is still unclear which model structures is most capable and suitable, how well they
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faculty position at the interface between machine learning and physics. Applicants will be considered at all ranks. We anticipate hiring faculty working on advancing machine learning methodology as applied
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-based rule-based checks with advanced machine learning architectures, specifically Long Short-Term Memory (LSTM) networks and Variational Autoencoders (VAEs). The researcher will use historical QC
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Vrije Universiteit Amsterdam (VU) | Amsterdam, Provincie Noord-Holland | Netherlands | about 1 month ago
EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description We are looking for a PostDoc who will do research on the intersection of machine learning (ML
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combining state-of-the-art machine learning with physicochemical knowledge and molecular modeling. Representative publications from our group include: https://doi.org/10.1038/s41467-025-63947-5 https
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combining state-of-the-art machine learning with physicochemical knowledge and molecular modeling. Representative publications from our group include: https://doi.org/10.1038/s41467-025-63947-5 https
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Show all breadcrumbs Postdoctoral Associate Position on Blockchain and Machine Learning in the Dr. Kuo Lab at Biomedical Informatics and Data Science, Yale University Tuesday, April 8, 2025
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, numerical method, and data-driven/machine-learning approaches, including: · Numerical simulation of kinetic equations: fast algorithms with stability/convergence analysis; · Data-driven and machine
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expertise in developing computational models and machine learning methods, as well as experience in repertoire data analysis. Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR8023