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position as HPC Systems Engineer – Security Architecture & Cluster Administration (m/f/d, E13 TV-L, 100%) The position is available in the team of the Machine Learning Science Cloud and runs until 31st
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Max-Planck-Institut für Struktur und Dynamik der Materie | Hamburg, Hamburg | Germany | 2 months ago
Computing Services, we are seeking an IT Specialist for Linux System Administration and HPC (m/f/d) Your position: The position is embedded within the IT Services team and works in close collaboration with
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Max Planck Institute for the Structure and Dynamics of Matter, Hamburg | Hamburg, Hamburg | Germany | 2 months ago
HPC (m/f/d) Your position The position is embedded within the IT Services team and works in close collaboration with the SSU Computational Science team. Serving as a key interface between enterprise IT
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of HPC or cloud computing. Practical experience with computer vision. Experience with databases, research data management, GIS or geospatial data processing. What we offer An opportunity to play an active
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Earth system modeling framework remains technologically advanced and capable of efficiently exploiting emerging HPC architectures. Emphasis will be placed on heterogeneous computing and the optimal use
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high-performance computing (HPC) environments and/or cloud-based data processing infrastructures Familiarity with workflow management systems (e. g. Nextflow) and workflow orchestration Experience with
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establish a research profile. Develop and execute innovative research projects. Develop, train, and evaluate modern machine-learning models on GPU/HPC infrastructure. Integrate AI methods with scientific
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framework of the HAMburg Ocean Carbon Cycle model (HAMOCC) which is part of the ICON Earth system modeling framework remains technologically advanced and capable of efficiently exploiting emerging HPC
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and optimization problems at unprecedented speed and scale. While high-performance computing (HPC) has become the backbone of large-scale power system simulation, emerging quantum computing technologies
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involving Prof. Dr. Michael Bader (TUM CIT, Hardware-aware algorithms for HPC) , Prof. Dr. Felix Dietrich (TUM CIT, Physics-enhanced Machine Learning) , and Prof. Dr. Hartwig Anzt (TUM CIT, Computational