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electrical engineering, computational engineering, or a related discipline A strong foundation in power system modelling and simulation Solid programming skills (Python, C++, or comparable languages) Interest
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of computer science, biology, physics, mathematics or a related field Programming skills in Python required (Numpy, Pandas, Scikit-learn, Pytorch) Hands-on experience in Deep Learning Demonstrated interest in working
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engineering, process engineering, chemistry or a comparable discipline Knowledge of hydrogen and energy research is an advantage High motivation to complete the doctorate within three years Very good
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to the FAIR data principles Your Profile: Master`s degree in astronomy, physics, computer science or equivalent degree Solid background in star and planet formation or small bodies of the solar system
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interdisciplinary PhD projects in the Simulation and Data Lab Digital Bioeconomy. Each project combines natural sciences with computational and data-driven approaches, focusing on topics such as plant carbon
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partner from data sciences provides data management and AI based Image analysis, an internal experimental group, and an internal simulation-sciences group (You+Supervisor+support by lab
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reports Develop and apply software tools Document software and data according to the FAIR data principles Your Profile: Master`s degree in astronomy, physics, computer science or equivalent degree Solid
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geophysics, physics, geoscience, computational geoscience, or related natural sciences with an overall grade of at least good Experience in programming (e.g., matlab, phyton, C/C++) Advanced knowledge
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international research contexts Your Profile: Excellent Master’s degree in mechanical engineering, energy systems, computational engineering, or a related field Strong background in numerical methods and applied
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be found on our website: www.fz-juelich.de/ibg/daten-ki/casa-sdl-dbe Your Profile: Master’s degree (or equivalent) in computer science, applied mathematics, physics, engineering, biology, plant and