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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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assessment criteria: Knowledge in energy technology, large language models (LLMs), deep learning, and Python programming. Meritorious qualifications include knowledge in power engineering, power electronics
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knowledge in programming (preferably in Python), personal characteristics, such as a creativity, thoroughness, and/or a structured approach to problem-solving are essential. Additional qualifications
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such as Matlab, or Python. Excellent command of spoken and written English. Additional qualifications Experience with modelling, simulation, and optimization of energy systems. Experience in thermodynamic
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and communication or related domains. Proficiency in programming (e.g., C/C++, OpenGL, Python) is required. Also, proficient, prolific, and ethical use of AI in everyday work is a requirement as
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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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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