230 machine-learning "https:" "https:" "https:" "https:" "https:" positions in Germany
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the development and application of probabilistic inference methods and machine learning techniques for quantitative uncertainty modeling and for the integration of heterogeneous climate data
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Infrastructure? No Offer Description Work group: IAS-8 - Datenanalyik und Maschinenlernen Area of research: PHD Thesis Job description: Your Job: We are looking for a PhD student in machine learning to work within
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Job related to staff position within a Research Infrastructure? No Offer Description PhD position on physics-based machine learning modeling for materials and process design Reference code: 2026/WD 1
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of visualisation, machine learning, and human-computer interaction under the joint supervision of both institutions. The position is shared by TU Wien and USTP and offers the opportunity to conduct research at both
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one of the following certificates: TOEFL minimum of 550 (paper-based test), 213 (computer-based), 79 (Internet-based) IELTS minimum of 6.5 CPE minimum level C CAE minimum level C https://www.math
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Gorlitz, Sachsen | Germany | about 1 month ago
Understanding (CASUS) is a German-Polish research center for data-intensive digital systems research. The Department of AI4Quantum – Machine Learning for Quantum Simulation and Computing is looking for a PhD
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like knowledge graphs, information extraction, machine learning or artificial intelligence in the context of scholarly data Publication of research and project results Your profile: Scientific University
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tools like ViennaRNA and NUPACK) and MD simulations (e.g., with GROMACS). Strong skills in statistical data analysis and machine learning in Python and R are expected, along with experience working in
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data Your Profile The ideal applicant has a strong background in bioinformatics and/or probabilistic machine learning, as well as experience in omics data analysis, and possesses solid English-language
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. The position involves close collaboration with experts in cardiovascular simulation and Scientific Machine Learning. Your tasks: Development and comparison of data driven models for the prediction of stresses in