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willingness to learn: High-performance computing (distributed systems, profiling, performance optimization), Training large AI models (PyTorch/JAX/TensorFlow, parallelization, mixed precision), Data analysis
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02.07.2025, Wissenschaftliches Personal The Professorship of Energy Management Technologies at TUM’s School of Engineering and Design is looking for a Postdoc (f/m/d) in Energy Informatics. You are
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Germany Application Deadline 15 Oct 2025 - 21:59 (UTC) 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
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Germany Application Deadline 5 Oct 2025 - 21:59 (UTC) 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
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Max Planck Institute for Gravitational Physics, Potsdam-Golm | Potsdam, Brandenburg | Germany | 2 months ago
Berlin, and the University of Potsdam. Currently, the ACR department operates a high-performance compute cluster, Urania, with ~6,050 cores, a high-throughput compute cluster, Hypatia, with ~12,000 cores
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results. Machine Learning skills to automise comparison process. Unbiased approach to different theoretical models. Experience in HPC system usage and parallel/distributed computing. Knowledge in GPU-based
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hydrodynamics and/or N-body simulations in the star and planet formation context Experience in the field with HPC system usage and parallel/distributed computing Knowledge in GPU-based programming would be
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methods, machine learning algorithms, and prototypical systems controlling complex energy systems like buildings, electricity distribution grids and thermal systems for a sustainable future. These systems
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31.07.2023, Wissenschaftliches Personal Within the Joint Academy for Doctoral Studies (JADS) program of Technical University of Munich and Imperial College London, the Professorship of Energy
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of acquisition, organization, compression, analysis, and visualization of georeferenced or geometric data in large scales. We put emphasis on methods of distributed computing, machine learning, image and text