56 computational-physics Postdoctoral positions at Technical University of Munich in Germany
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, Physics, Biophysics, Molecular Biology, or related filed Strong expertise in bioanalytics and peptide synthesis Experience with automated liquid handling / high-troughput platforms Experience in managing
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these mechanisms, as they reca-pitulate key aspects of embryonic development and tissue morphogenesis in vitro. The group of Prof. Bausch investigates the physical principles underlying these emergent processes and
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qualifications: • A completed Master’s degree (or equivalent) in a relevant discipline, such as philosophy, neuroscience, psychology, medicine, law, social sciences, computer science, or a related field • Strong
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closely with various institutions and companies from all over the world, especially the USA, the UK, and Germany. Your Profile: - Ph.D. in (electro)chemistry, material science, engineering, physics, or a
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while keeping the grid reliable and secure. Our research method is engineering-oriented, prototype-driven, and highly interdisciplinary. Our typical research process includes the evaluation of existing
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24.02.2022, Academic staff The Munich Quantum Valley aims at developing a full quantum computing stack, from the application level to the physical quantum hardware. Within this interdisciplinary
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; an extension of an additional 2 years is possible. TASKS: Mathematical and physical modeling to determine greenhouse gas and pollutant emissions in cities using novel atmospheric measurements (MUCCnet
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-average doctoral degree (PhD or equivalent) in management, organizational psychology, sociology, economics, business informatics, or a related field, • With a solid knowledge of empirical research methods
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. Requirements: Completed university degree in computer science or applied mathematics, remote sensing, geophysics, physics, or related areas Expertise in computer vision and/or machine learning (deep learning
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PhD/Postdoc position in trustworthy data-driven control and networked AI for rehabilitation robotics
of such systems, taking particularly into account model uncertainties as well as limitations pertaining to acquisition of data, communication, and computation. We apply our methods mainly to human-robot-teams