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on the hydrological cycle, large-scale data integration, and AI-based approaches in groundwater and surface water. We expect you to strengthen our collaboration with universities, agencies and international research
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to work in a large international collaboration while advancing your own research; and a good command of spoken and written English. Experience with data analysis in astroparticle, particle or cosmic-ray
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international reach. It’s a large faculty but also versatile, so we can often make unique connections by combining different disciplines. This is reflected in ME’s outstanding, state-of-the-art education, which
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made significant progress in this direction by merging machine learning interatomic potentials (MLIPs) trained on density functional theory (DFT) data, and enhanced sampling techniques to reach the
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to next-generation 2D gas sensors. You will manage large-scale simulations run on world-class supercomputing facilities alongside AI algorithms and data analytics tools, and share your results with
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3 Jul 2026 Job Information Organisation/Company CNRS Department Laboratoire de Physique Research Field Environmental science Environmental science » Earth science Environmental science » Global
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Learning for Electron–Phonon Interactions and Wannier-Based Hamiltonians The ELPH-ML project, led by Dr. Ransell D'Souza at the Department of Chemistry and Materials Science, Aalto University, and the Data
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molecular information with multi-omics data, digital pathology and artificial intelligence, your work will generate new insights into pharmacodynamics, efficacy biomarkers and toxicity mechanisms that cannot
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is valid for applicants from: all countries For the winter semester: until 31 August More information on application periods Please find more details on this website . Combined Master's degree / PhD
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Details Title Postdoctoral Fellow in Computer Science — From Theory to Practice: Reinforcement Learning for Large Scale Foundation Model Post‑Training School Harvard John A. Paulson School of