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Heidelberg Institute for Theoretical Studies (HITS gGmbH) | Heidelberg, Baden W rttemberg | Germany | 3 days ago
. High-risk, high-gain projects are encouraged. Selected candidates will interact with existing groups at HITS while developing and pursuing their independent research projects. The institute and research
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, validated through simulations and experimental testbeds. Become a part of our team and join us on our journey of research and innovation! Be part of change Development and evaluation of algorithms
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. Selected postdocs will collaborate with group leaders at HITS while developing and pursuing their independent research projects. The institute and research focus The Heidelberg Institute for Theoretical
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. The successful candidate will pioneer new algorithms for graph-structured data, revisit classical graph problems through the lens of modern machine learning, and help define the next generation of generative
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upgrade, luminosity measurements, the alignment of the Tracker and other calibration activities, as well as algorithmic work and shifts for the detector operation.The DESY CMS group is seeking to hire two
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Systems At the Institute of Climate and Energy Research – Energy Systems Engineering (ICE-1), our focus is on developing models and algorithms for simulating and optimising decentralised, integrated energy
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Responsibilities Conduct research in computational methods for environmental and engineering applications. Develop and analyze numerical algorithms, reduced-order models, and machine-learning-enhanced simulation
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modeling and simulation • Development in Finite element and alternative discretization methods (e.g. Lattice Boltzmann methods) • High-dimensional algorithms and high-performance computing
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Develop event-driven algorithms and software components for autonomous experiment control and adaptive image acquisition Build scalable, maintainable, and open-source software for high-throughput image
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, and unmodeled dynamics remains a key challenge. This position focuses on developing and validating methods that jointly address safety, performance, and reliability of learning-based control and