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Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg | Magdeburg, Sachsen Anhalt | Germany | 26 days 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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data to answer relevant questions and solve real-world problems. It brings together fundamental, methodologically driven research in optimization, machine learning, and artificial intelligence with
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applications as PhD Student Position (f/m/d) (Ref. 25/11) in the Leibniz Junior Research Group “Probabilistic Methods for Dynamic Communication Networks“ (Head: Prof. Dr. B. Jahnel) starting as soon as possible
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materials. This will be done in collaboration with Prof. Dominik Bucher at the Technical University of Munich, and you will be spending 2-6 months in his laboratory. Responsibilities and qualifications
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section Energy Technology and Computer Science, where you will have around 20 colleagues with a mix of research and industrial experience. We work with research, innovation, technology implementation, and
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. This includes overseeing local plasma experiments, such as the NORTH tokamak and a linear plasma device, and contributing to the design and optimization of antennas for ion cyclotron heating and gyrotrons
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various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly
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The SigCom research group of SnT, headed by Prof. Symeon Chatzinotas, focuses on wireless/satellite communications and networking. The research areas focus on the formulation, modeling, design, and
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The SnT Automation & Robotics Research Group is hiring a motivated PhD candidate for the bi-national project DOMINANTS (Dexterity-Oriented Methodology in Optimized Design and Control of Soft Aerial
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consumption while guaranteeing optimal power production. You will work on the cutting edge of both wind energy and machine learning, two of the fastest growing scientific disciplines, to develop graph-based