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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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of industrial processes. The Department of Computational Fluid Dynamics is seeking a PhD Student (f/m/d) to contribute to “Experimental analysis and simulation of flow-induced vibration in gas-liquid two-phase
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. Hoffmann’s research group, an innovative project is being conducted on the processing and analysis of seismic data from a large-scale Distributed Acoustic Sensing (DAS) network. This network is installed
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tasks: You will work together with renowned astrophysicists and computer scientists in the DFG-funded “Dynaverse” Excellence Cluster You will invent, implement, and benchmark novel AI tools (reinforcement
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to you on the website: https://tu-dresden.de/karriere/datenschutzhinweis . This project has received funding from the European Union’s Horizon Europe research and innovation program under the MARIE
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infrastructure research programme distributed across several institutes and universities in Germany. The programme aims at innovating the data landscape available for social science research by improving
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2038 - 03:14 (UTC) Country Germany Type of Contract To be defined Job Status Other Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff
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training schemes for large models on high-performance computers like JUWELS and JUPITER at the Jülich Supercomputing Center. If you`re passionate about AI research and eager to make a real-world impact, we
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at the Technical University of Munich (TUM) invites applications for one PhD position. The student will work on developing scalable distributed preconditioners in Ginkgo (https://github.com/ginkgo-project/ginkgo
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, safe and socially just energy supply system based on renewable energies. We contribute to this with our research priorities of energy supply, energy distribution, energy storage and energy use. We