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Theory aims to understand the properties of strongly interacting/correlated matter such as the spectrum of QCD, and develops algorithms and implementations for various high-performance computing (HPC
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. Particularly advantageous Experience with modern software-engineering practices, e.g., git, automated testing, packaging, documentation and code review. Experience with GPU computing or high
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-performance computing to high-performance analytics; from data integration to data-related topics such as uncertainty quantification, model-order reduction, or multi-fidelity methods. The primary fields of
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publicly available datasets to interpret results in a robust biological context Ensure reproducibility, data management, and documentation of computational workflows in high-performance computing
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structures, high-performance computing, and quantum algorithms. Beyond this research, we aim to support com-putational thinking and computational problem-solving across the Earth sciences at a large
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environment for research data management, incl. research storage, quota management, repositories, offboarding and archiving Liaison, onboarding and user management for external high-performance
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hydrogen-fueled combustion systems. The project combines the expertise of 12 European research institutions in advanced experiments, high-fidelity simulations, theory, automatic differentiation, and
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-temperature scanning tunnelling microscopy, ARPES, Kerr microscopy, femtosecond pump-probe and terahertz spectroscopy, electron microscopy, positron annihilation. Theory: high-performance computing, and
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Informatics, Mathematics, or a related field (e.g. Computational Science/Engineering) Strong knowledge of machine learning, Scientific Computing (particularly linear algebra and numerics), and High Performance