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-mobility, automation, climate solutions, and energy efficiency. Research at the Centre encompasses a diverse array of fields such as cyber-physical systems, mechanical structure integrity, renewable energy
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the scalability and robustness of AI in complex environments which is a major step towards the digital transformation of the manufacturing industry. Motivation Automation is key to meeting the growing demand
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complex networks by merging physical and cyber levels. This is a unique opportunity to explore the synergies between the physical and cyber domains in the realm of space engineering and investigate how can
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programme No Description/content The IMPRS for "Quantum Dynamics and Control" is a graduate school with its headquarters at the Max Planck Institute for the Physics of Complex Systems in Dresden/Germany and
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of this state-of-the-art facility, which is expected to be fully operational by 2035/2036 and will include advanced laboratories for diagnostics and research, cutting-edge biosafety systems, and complex technical
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to the complexity of the mathematical models that describe them. The current consensus is that there are three “types” of viscoelastic chaos: modified Newtonian turbulence, elastic turbulence, and elasto-inertial
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Everyone is talking about artificial intelligence. But who is developing the necessary chips? We are, for example! Would you like to help drive the development of a new highly efficient AI hardware
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for classical communication while producing quantum-correlated photon pairs for secure channels. The Emergent Photonics Research Centre is a 500 m² university facility dedicated to complexity in Photonics
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2025 Apply now Join the Institute for Chemical Neuroscience external link (iCNS) to study molecular changes in the human brain linked to psychiatric symptoms. In the brain, the complement system plays
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engineering related discipline. The project is suitable for Engineering or Physics graduates, with a strong background in Fluid Mechanics, Heat Transfer and preferably with experience in computational modelling