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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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system modelling. Solid knowledge in mathematics, physics, thermodynamics, energy technology, optimization, and programming for system modelling, with experience in tools such as Matlab, or Python
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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 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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for candidates who have: Strong programming skills, particularly in Python Solid analytical and mathematical abilities Experience with machine learning Strong communication skills and proficiency in English The
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have some experience with scientific programming, in particular in Python, PyTorch or similar, in particular with respect to advanced data analysis or modelling operations. PhD students at the department
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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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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