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Job description: DESY The CMS Quantum Computing group develops generative machine learning models for detector simulations, specifically the simulation of showers in calorimeters: Proof-of-principle
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interests in applied statistics, machine learning, or computational biology are encouraged to apply. For more information, please visit our website https://ds.dfci.harvard.edu/postdocs to view the list
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 20 days ago
programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Area of research: PHD Thesis Job description:PhD Position in Machine Learning for Single-Cell Genomics (f
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grasslands and evaluation of land-use intensity, Expertise in classification with machine-learning methods, statistics, spatial analysis and land-use modeling, Experience and interest in conducting fieldwork
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with modern machine learning and AI technologies to effectively address large-scale problems. About the research project We are seeking a highly motivated Postdoc to join our group in developing
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and machine learning”, UMO-2022/46/E/ST4/00377, Rafał Szabla Position description: The Faculty of Chemistry of the Wrocław University of Science and Technology is looking for a candidate for the
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and Liu, Supervised learning in physical networks: From machine learning to learning machines, PRX 11, 021045 (2021) [2] Stern and Murugan, Learning without neurons in physical systems, Ann Rev Cond
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, France [map ] Subject Areas: Machine Learning / Machine Learning Mathematics Probability Statistical Physics Statistics Appl Deadline: 2025/12/21 04:59 AM UnitedKingdomTime (posted 2025/11/25 05:00 AM
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Date: August 15, 2026 (negotiable) Specialty Areas: Computational Linguistics, Language Acquisition, Cognitive Modeling, Machine Learning The Department of Linguistics at the University of Michigan
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Familiarity with immune profiling and systems immunology in infectious diseases or critical illness, including sepsis Experience with machine learning approaches for biomedical datasets Planning and preparation