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, United States of America [map ] Subject Area: Quantum Computing / Quantum Computing Appl Deadline: (posted 2026/01/20, listed until 2026/06/28) Position Description: Apply Position Description Occupational Summary
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. The researcher(s) will be provided access to state-of-the-art supercomputing facilities with advanced GPU and data storage capabilities. Additionally, opportunities will be available for collaborations. Duties
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | 1 day ago
. What we offer State of the art on-site high performance/GPU compute facilities Competitive research in an inspiring, world-class environment A wide range of offers to help you balance work and family
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%). You will work on the extension of the DUNE-FEM package to support computations on GPU hardware with various types of Finite Element methods. This work is embedded in a research project considering
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significant computational component in deploying multi-GPU codes to efficiently train on the large, densely-connected and graph-structured data encountered in our systems of interest. Your contributions would
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development. You’ll have access to state-of-the-art high-performance computing infrastructure and GPU clusters essential for conducting cutting-edge AI, software engineering, and security research. Salary range
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: Knowledge on floating point arithmetic and mixed/reduced precision computing techniques Experience with programming GPUs and/or other accelerators Proficiency in mathematical reasoning and numerical analysis
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have dedicated funds for traveling, computing, publications, etc. The preferred starting date is Fall of 2026. Applicants need to submit a cover letter, curriculum vitae, publication list, and a brief
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to support computations on GPU hardware with various types of Finite Element methods. This work is embedded in a research project considering structure preserving Finite Element methods for multiphase flows
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linear algebra computations, building software for scientific applications using GPUs (Graphics Processing Unit), multi-threading and parallelism, numerical discretization methods (finite differences