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nanostructures and networks. These systems will have tunable chemical and photophysical properties for the translational development of platform technologies in the advanced materials sciences. This is a highly
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focus on deep networks for solving inverse problems, learning robust models from few and noisy samples, and DNA data storage. The position is in the area of machine learning, with a focus on deep learning
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: - QUANTITATIVE VERIFICATION: analysis of probabilistic systems (Markov decision processes, stochastic games, chemical reaction networks), automata theory and temporal logic, machine learning in verification
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network with partners from science and industry and take on responsibility at the chair right from the start. In your role as a post-doc, you will combine team and institute-oriented tasks with in-depth
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pages or friendships between users in a social network. Due to the large variety in data science tasks performed with graph-structured data, different specialized systems have been developed, such as
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scientists of the Futurelab offers an outstanding opportunity for networking and the development of followup projects. The position will be remunerated between W1 and W3 equivalent according to your
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., for quantum computing, microfluidics, or conventional circuits and systems. Our focus on interdisciplinary partnerships and networks will enable you to meet many interesting people (at places all over the world