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Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg | Magdeburg, Sachsen Anhalt | Germany | about 2 months ago
The Department of Process Systems Engineering (Director: Prof. Dr.-Ing. Kai Sundmacher) at the Max Planck Institute for Dynamics of Complex Technical Systems is inviting applications for the PhD
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Master's degree / PhD programme No Joint degree / double degree programme No Description/content ENWAT (Environment Water) is facilitated by the Civil and Environmental Engineering Sciences Department
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work in state-of-the-art laboratories and clean rooms. The role involves working in a cryogenic laboratory environment and following specific clean room protocols Master`s degree in physics or electrical
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activity (work, studies, etc.) in Germany for more than 12 months in the last 36 months Master’s degree in physics, electrical/electronic engineering, computer science, mathematics, or a related field
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activity (work, studies, etc.) in Germany for more than 12 months in the last 36 months Master’s degree in physics, electrical/electronic engineering, computer science, mathematics, or a related field
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period of 36 months. The Fraunhofer Institute for Chemical Technology ICT in Pfinztal near Karlsruhe is one of approx. 75 Fraunhofer institutes in Germany. Its department for Applied Electrochemistry
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fields (e. g. physics, computer science, electrical/electronic engineering, chemistry etc.). The knowledge of Python, C or other programming languages in use for accelerator facilities is advantageous. We
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discipline relevant to our research fields (e. g. physics, computer science, electrical/electronic engineering, chemistry etc.). The knowledge of Python, C or other programming languages in use for accelerator
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Brandenburg University of Technology Cottbus-Senftenberg • | Cottbus, Brandenburg | Germany | about 16 hours ago
Transformation Processes. The programme is affiliated to the Faculty of Architecture, Civil Engineering and Urban Planning. Doctoral students conduct individual research in the fields of heritage conservation and
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in physics, electrical/electronic engineering, computer science, mathematics, or a related field Strong background in machine learning, particularly deep learning and optimization methods Excellent