51 postdoctoral-soil-structure-interaction-fem-dynamics Postdoctoral positions at Technical University of Munich
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for research, and #9 in Europe for M.Sc. programs on entrepreneurship. The TUM Campus Heilbronn is a dynamic organization whose goal is to achieve excellence in research, teaching and impact. The
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rankings in research and teaching. Our group “Sustainable Energy Materials” concentrates on the preparation of heterogeneous catalysts and the understanding of structure-performance indicators in
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the student solutions using machine learning. We offer: - International and gender-balanced group - Dynamic and collaborative work style - Flexible working hours, home office possibilities etc. - Full-time
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sensors and apply them to novel applications. Technically, your work will involve the design and construction of optics and electronics, clean room fabrication and software development, as well as theory
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Euro / year + benefits). 3D Semantic Scene Understanding: The world around us exists spatially in 3D, and it is crucial to understand real-world scenes in 3D to enable virtual or robotic interactions
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in static and dynamic 3D reconstruction, semantic scene understanding, and generative models for photo-realistic image/video synthesis. Overall, the main focus is on high-impact research with the aim
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Euro / year + benefits). 3D Semantic Scene Understanding: The world around us exists spatially in 3D, and it is crucial to understand real-world scenes in 3D to enable virtual or robotic interactions
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field of additive manufacturing of metallic structures. The main focus is on developing and characterizing metallic high-performance materials for/through additive technologies by means of experiments and
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interactions with such environments. We investigate machine learning approaches to infer semantic understanding of real-world scenes and the objects inside them from visual data, including images and depth/3D
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investigate methods that eventually will automate crucial design steps. In addition, we are developing simulators (on various abstraction levels; using, e.g., Computational Fluid Dynamics) which enables us to