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and data analytics (including machine learning and deep learning); from high-performance computing to high-performance analytics; from data integration to data-related topics such as uncertainty
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of potentially novel modes of protein binding is possible in collaboration with other members of the lab. Desired (but not absolutely required) skills: programming in python, machine learning, and experience in
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learning and data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms
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applications for a PhD Student or Postdoc Position (f/m/d) for any of the following topics: Combining non-equilibrium alchemistry with machine learning Free energy calculations for enzyme design Permeation and
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play a central role in this interdisciplinary initiative. They will: Develop and apply machine learning (ML) methods – including surrogate modeling, feature extraction, and inverse design algorithms
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direction (possibly forming spontaneous “lanes”), crossing, and opposite flows. For single-lane vehicular traffic, the model should revert to a car-following model. In cooperation with the supervisor Dr
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dynamics, data science, and machine learning are beneficial. Please submit your detailed application with the usual documents by August 15, 2025 (stamped arrival date of the university central mail
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play a central role in this interdisciplinary initiative. They will: Develop and apply machine learning (ML) methods – including surrogate modeling, feature extraction, and inverse design algorithms
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disciplines strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation and the ability to work independently with
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civil/electrical/control engineering or mathematics or related study programs with a solid basis in choice modelling and/or reinforcement learning, with knowledge of MATSim is advantageous. Description