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qualified candidates, regardless of gender. RWTH Aachen University and Forschungszentrum Jülich are recognized as family-friendly institutions and provide dual career programs to support partner hiring. We
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, computer science, mechanical engineering or electrical engineering Ideally, you have already gained some programming experience with Python and have already tried your hand at data science You may even have used
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. Committed and active participation in teaching in the degree programs of the Faculty of Medicine is expected. As this is an endowed professorship, the teaching commitment is 2 semester hours per week (SWS
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with other research groups for chip applications, e.g. in physics, life sciences, materials sciences, medicine, and machine learning. Chip Design is also a focus of the Master′s program in Computer
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Max Planck Institute for Chemical Energy Conversion, Mülheim an der Ruhr | M lheim an der Ruhr, Nordrhein Westfalen | Germany | about 2 months ago
. The position is available immediately, the starting date is flexible till January 2026. The doctoral researcher will work on a 3-year-doctoral program. The successful candidate will be supervised by Prof. Dr
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science or a comparable subject You have extensive knowledge of at least one programming language You understand the structure and operation of electrical power systems You have excellent command
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and circular economy You have successfully acquired and managed third-party funded projects and have a track record of publications in recognized, peer-reviewed journals Familiarity with programming
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Biology, Computer Science or related studies) Experience in Python with PyTorch (or equivalent) programming Experience in sequencing data analysis Basic knowledge in machine learning Experience with linux
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-based environments (e.g. Kubernetes) What you bring to the table You are currently enrolled in a degree program with a focus on computer science for at least three semesters You have advanced programming
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natural sciences expertise in materials science and materials engineering, in particular methods of computational material science (e.g. DFT, CALPHAD) programming skills, e.g. Python basic knowledge of data