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Via Multiple Noncovalent Interactions” in the second funding phase at the Martin Luther University Halle-Wittenberg will start with a highly interdisciplinary and ambitious research program in November
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Description The Research Training Group (in German: Graduiertenkolleg, GRK) RTG2670 “Beyond Amphiphilicity: Self-Organization of Soft Matter Via Multiple Noncovalent Interactions” in the second
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) Research area: Large Language Models (LLMs), knowledge graphs (KGs), commonsense knowledge Tasks: foundational or applied research in at least one of the following areas: LLMs, KGs, knowledge extraction
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master’s degree or diploma in physics, applied mathematics, or a relevant engineering discipline Good programming skills and experience with numerical modeling Interest in performing experiments Excellent
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Engineering, Operations Research, Civil Engineering, Computer Science, Data Science or a related field, from a university/department with a strong international research reputation Strong mathematical and
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, numerical information field theory, CMOS detector technology and UBIK (see https://arxiv.org/abs/2409.10381) Modeling & Simulation: Development of fast, accurate and differentiable digital twins of CMOS
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Max Planck Institute of Molecular Cell Biology and Genetics, Dresden | Dresden, Sachsen | Germany | about 2 months ago
Job Code: 2025-Mathematics-ResearchManager-1120 Job Offer from June 27, 2025 We are seeking a proactive, analytically sharp and strategically minded person to join our mathematics-led research team
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Design and implement optimization techniques for full-stack improvement of quantum algorithms Model major sources of experimental error for control theory or for error mitigation techniques Scientific
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, their achievements and productivity to the success of the whole institution. At the Faculty of Mathematics, Institute of Scientific Computing, within the Dresden Center for Computational Materials Science (DCMS
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Field of study: computer science, mathematics, software design, software engineering, technical computer science or comparable. Machine Learning (ML) models are reaching a maturity level that allows