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Postdocs in Data-Driven Product Realization Reference number REF 2026-0393 Join us for an exciting postdoctoral position to shape the future of data-driven product realisation in close collaboration
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Are you interested in data-driven modelling and optimisation of District Heating Systems and can you contribute to the development of our Villum Synergy project, “ Recycling waste heat: Graph-based
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interfaces and defects. This research will combine electronic structure methods, artificial intelligence, and data-driven techniques to understand and engineer novel materials for next-generation
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Researchers in AI-driven atomistic modeling and AI-accelerated cheminformatics to join the Otaniemi Center for Atomic-scale Materials Modeling (OCAMM), hosted by the Department of Chemistry and Materials
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algorithms and software tools for visualizing and analyzing materials characterization data Develop novel, data-driven materials characterization workflows Advance understanding of process-structure
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18,500 people, including over 14,000 students and 4,000 researchers from more than 120 different countries. Postdoctoral Researcher in Data-driven X-ray Nanoimaging for Semiconductor Metrology
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PhD / Postdoc position | AI-Driven Molecular Modeling for Atmospheric Organic Reactions and Multiphase/Interfacial Chemistry Young Researchers Mainz Chemistry Earth Sciences and Climate Research Job
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Center for Drug Evaluation and Research (CDER) | Southern Md Facility, Maryland | United States | about 9 hours ago
Mechanistic Modeling and Clinical Data Analysis of Emerging Drugs Organization U.S. Food and Drug Administration (FDA) Reference Code FDA-CDER-2026-0176 How to Apply To submit your application, scroll to the
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, and materials kinetic processes in materials. Design and perform systematic computer simulations on LLNL supercomputers to establish the foundational understanding of thermodynamic and kinetic
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, and materials kinetic processes in materials. Design and perform systematic computer simulations on LLNL supercomputers to establish the foundational understanding of thermodynamic and kinetic