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that come along with large-scale experiments. We offer leading interdisciplinary research between domain research fields and computer/data science or applied mathematics; research at world-leading, large
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Max Planck Institute for Intelligent Systems, Tübingen, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | about 1 month ago
) | Computer Vision The Optics & Sensing Laboratory (OSLab) at the Max Planck Institute for Intelligent Systems in Tübingen (Germany) has an open position for a Doctoral Researcher for the project “WeGaze
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recovery efficiency. Working closely with our experimental collaborators, you will analyse and model experimental data to efficiently explore the large design space of membrane functionalization and
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workflow that maps first-principles electronic-structure data onto predictive atomistic spin-Hamiltonians and device-scale dynamical models. The candidate will run high-throughput, relativistic DFT
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large environmental and ecological data sets, incl. empirical, remote-sensing and simulated model data knowledge in programming languages (UNIX, C, or similar) and script-based programming (R, Python
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, 100% funded PhD student position to fill starting around June 2026. Research is to be in the field of computational methods in nonlinear and large scale optimization / inverse problems or in novel
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Gorlitz, Sachsen | Germany | about 1 month ago
14 Mar 2026 Job Information Organisation/Company Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association Research Field Other Researcher Profile Recognised Researcher (R2) Established
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crystalline materials contains the information on dynamic and static disorder. Relating this information to the underlying structural disorder is a challenging task, particularly in the case of single crystal
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RESPONSIBILITIES: Implementing laboratory and computational workflows for large-scale biological studies Collecting experimental and high-throughput data Characterisation of molecular and cellular mechanisms
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field * Strong background in mathematical and computational sciences * Experience with large-scale machine learning, foundation models, or data-centric AI is a plus * Driven, with a strong work ethic and