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Field
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for the analysis of stable carbon isotopes in methane using the Picarro system. You will collect quantitative data for MPn in water samples from the Baltic Sea and the Warnow Estuary in order to investigate its
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15.09.2025, Wissenschaftliches Personal The Chair of Marketing Analytics, which is part of the Heilbronn Data Science Center and the TUM School of Management at the TUM Campus Heilbronn, is seeking
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vehicle. Multiscale simulations of the downstream expansion behaviour of the residuals for different atmospheric layers. Definition of suitable interfaces to process data for the climate models. Expected
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Leibniz-Institute for Food Systems Biology at the Technical University of Munich | Freising, Bayern | Germany | 28 days ago
10 Nov 2025 Job Information Organisation/Company Leibniz-Institute for Food Systems Biology at the Technical University of Munich Research Field Biological sciences Chemistry » Computational
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University of Munich Qualifications The applicants should possess: An excellent or very-good university degree in Economics Strong analytical and methodological skills with a focus on quantitative data
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mathematics Proficient in programming (Python and C++) Fluent in written and spoken English; knowledge of German is an asset Strong analytical and independent working style Excellent teamwork and communication
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in high-performance computing, numerical simulation Fluent in written and spoken English Independent, analytical, and team-oriented working style You are independent, motivated, and passionate about
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Strong analytical and independent working style Excellent teamwork and communication skills You are independent, motivated, and passionate about shaping the energy transition—if this describes you, we
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of the re-entering vehicle. Multiscale simulations of the downstream expansion behaviour of the residuals for different atmospheric layers. Definition of suitable interfaces to process data for the climate
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and data analytics (including machine learning and deep learning); from high-performance computing to high-performance analytics; from data integration to data-related topics such as uncertainty