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and problem-solving skills are important, and previous experience or interest in coding (for example in R or Python) would be a clear advantage since the project involves handling and interpreting
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molecular simulations. Previous hands-on experience in more than one of the following methods is considered an advantage: molecular simulations, Python programming, machine learning, or quantitative analysis
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, multiphase flows, or similar areas. A deep understanding of the physics and dynamics of fluid and thermal systems. Proficiency in programming and data analysis tools, such as Python and MATLAB (or equivalent
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Python for scripting and data analysis, metabolite ID via MS/MS and annotation (e.g. SIRIUS, HMDB, authentic libraries etc.), statistical uni- and multivariate analysis, data visualization (PCA score
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. The required expertise includes raw UPLC-MS-collected data preprocessing with XCMS, MZmine or MSDIAL, normalization procedures, proficiency in R and/or Python for scripting and data analysis, metabolite ID via
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of energy-aware planning and scheduling in manufacturing, -experience in programming (Python, C/C++, Java, etc.) and implementing intelligent automation, -previous participation in EU or international
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related field, Knowledge in fluid mechanics and heat transfer, Programming skills (Python, MATLAB or equivalent), Strong English communication skills. Experience in multiphase flows, modeling, or AI methods
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. ability to code MBSE models in Capella. proficiency in Python programming. Application Welcome with your application, no later than October 7, 2025, including: Motivation letter CV Certified diplomas
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learning, mathematical statistics, optimization, and robotics. Experience from programming in C/C++ or Python is also meritorious. Willingness to work in an inter-cultural, international, and diverse group
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robotics, machine learning, and control is essential. Applicants should also demonstrate: High academic achievement in relevant undergraduate and graduate courses Proficiency in programming (C/C++, Python