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available in the further tabs (e.g. “Application requirements”). Programme Description The Baden-Württemberg-STIPENDIUM for Students is a programme established by the Baden-Württemberg Stiftung . You can
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Max Planck Institute for Plasma Physics (Garching), Garching | Garching an der Alz, Bayern | Germany | about 1 month ago
the EUROfusion Programme Manager. These are your responsibilities Managing correspondence, including the issue of calls for participation Managing and updating distribution lists within EUROfusion
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universities, the Helmholtz Association and Fraunhofer Society. Teaching language English Languages English (100%) Mode of study Less than 50% online Programme duration 8 semesters Beginning Winter semester
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(TIB ) – Leibniz Information Centre for Science and Technology – Program Area D, Open Research Knowledge Graph, is seeking a Postdoctoral Researcher (Postdoc) - Artificial General Intelligence (AGI
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Your Job: Investigate current challenges and bottlenecks in power flow analysis for large scale electrical distribution grids Apply machine learning/AI or surrogate modeling (e.g., neural networks
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) Time series modeling, forecasting, and real-time monitoring in dynamic bioeconomic systems Data-driven modeling and intelligent control in bioeconomic systems Out-of-distribution (OOD) generalization in
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The Fraunhofer Institute for Digital Medicine MEVIS is a world-leading and internationally connected research center for computer assistance in medicine. With about 140 employees, our mission is to
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individual for a Team Lead Position “Data Curation Unit” in Helmholtz Imaging Reference number: 2026-0035 As part of a distributed cross-center structure, the DKFZ lead will co-develop and implement a unified
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, Statistical Physics, Genome Annotation, and/or related fields Practical experience with High Performance Computing Systems as well as parallel/distributed programming Very good command of written and spoken
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, or similar domains) is a plus Solid understanding of cloud architectures and ML-Ops (AWS, Azure, or GCP) Familiarity with privacy-preserving or distributed learning approaches (e.g. Federated Learning) Comfort