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(4DSTEM). This approach will combine three-dimensional charge distribution data, generated through atomistic simulations, with machine-learning-driven modelling to guide and refine the phase reconstruction
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profile is shaped in particular by five high-profile areas. About Minds, Media, Machines Minds, Media, Machines (MMM) is one of the five interdisciplinary, high-profile areas that largely define
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mechanisms occurring in these materials and their synthesis over all relevant length scales (e.g., cutting-edge ab initio methods, atomistic simulation methods, multi-scale modelling, machine learning) High
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12.01.2026, Academic staff The Professorship of Machine Learning at the Department of Computer Engineering at TUM has an open position for a doctoral researcher (TV-L E13 100%; initial contract 1.5
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applicant has a strong background in bioinformatics and/or probabilistic machine learning, as well as experience in omics data analysis, and possesses solid English-language skills. Experience with
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Infrastructures Didactics of Informatics Digital Humanities Distributed Systems High-Performance Storage Machine Learning Medical Informatics Neural Data Science Practical Informatics Scientific Information
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science and information science techniques. Several areas of computer science and mathematics play important roles: data management and engineering, machine learning and data analytics, signal and image
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, leveraging a principled combination of passivity-based control methods, machine learning, and human-in-the-loop systems to enable robust teleoperation in uncertain and delayed communication environments. Key
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plate array microscope for simultaneous time-lapse video microscopy, enabling high-throughput single-cell analyses of rapidly migrating cells. You will be responsible for Develop new machine learning
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of visualisation, machine learning, and human-computer interaction under the joint supervision of both institutions. The position is shared by TU Wien and USTP and offers the opportunity to conduct research at both