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background in Statistical Mechanics and to mostly focus on analytical work and the development of novel quantitative methods for active matter, and to a lesser extent, on computer simulations of active fluids
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-party research funding are expected. We are particularly interested in a candidate in any field of economics who leverages state-of-the-art machine learning and causal inference methods to innovative
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: - Quantum computing with qudits, quantum error correction and fault-tolerance - Quantum optics of trapped ions and Rydberg atom arrays - Numerical tensor network techniques - Topological order and (de
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of targeted therapies. Analyzing high-dimensional single-cell data has its own statistical and computational challenges, and standard tools often cannot be applied. The purpose of the position and goal
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on both fundamental magnetic interactions and applications for efficient energy conversion. We use element-specific methods such as X-ray absorption spectroscopy at synchrotron radiation sources and
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. The successful candidate will apply molecular, imaging, and electrophysiological methods to investigate the molecular mechanisms of somatic mechanotransduction. We use genetic mouse models and human cells to gain
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: Excellent Master’s degree (or equivalent) in computer science, engineering, or related disciplines (typically mathematics, physics). For Postdoc applicants: Excellent track record in computer
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methods for the design, verification, and test of circuits and systems for conventional as well as alternative and post-CMOS computing technologies. Besides that, we have successfully applied the methods
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: Dynamical Systems Control Theory Formal Methods Reachability Analysis Computational Geometry Context The applicant will be directly advised by Prof. Matthias Althoff (https://www.ce.cit.tum.de/cps/members
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Centre, the Neutron-SimLab or various physicochemical characterization methods and workshops. The opportunity to help shape a new department. Access to the infrastructure of the Institute