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Field
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-oriented system solutions for the entire spectrum of industrial tasks – from product development to the production process, maintenance of capital goods, and recycling of products to the design and
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Office, childcare services, and dedicated programs for personal and career development. We look forward to receiving your application no later than February 6, 2026. All information about YIG Prep Pro
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image analysis to establish objective, fast, and scalable testing methods for the textile and cosmetics industries. Your tasks Development and implementation of AI/ML models (Deep Learning, Computer
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Max Planck Institute of Immunobiology and Epigenetics, Freiburg | Freiburg im Breisgau, Baden W rttemberg | Germany | 3 months ago
component Professional training and development opportunities Good public transport connections and subsidy for job ticket Challenging work in a modern working environment Mobile working at a location of your
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reactions using an additive based screening approach. 3) Development of a multi-objective Bayesian optimization algorithm for the reoptimization of reactions. 4) Application of the reoptimized key reaction in
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digitization. More than 400 employees – including around 100 students – from over 50 countries work at nine locations in scientific and non-scientific teams on the development of innovative methods to accelerate
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. If you are an experienced researcher with a strong background in mechatronics, robotics, or control systems eager to lead research, development, and system integration of service humanoid robots with a
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networking and participation in advanced NMR methodology development with direct biomedical applications The position is suitable for disabled persons. Disabled applicants will be given preference in case
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part of the Rashid-3 rover by MBRSC (UAE) and is expected to be launched to the Moon in 2028. Your tasks will include instrument development from TRL 5 to 8, test and characterisation of the instrument
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11.09.2025, Academic staff A Ph.D. position is available in the Professorship of Data-driven Materials Modeling to contribute to the development of efficient, certifiable, and practical solutions