37 condition-monitoring-machine-learning Postdoctoral positions at UNIVERSITY OF VIENNA
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50 Faculty of Life Sciences Startdate: 18.08.2025 | Working hours: 40 | Collective bargaining agreement: §48 VwGr. B1 lit. b (postdoc) Limited until: 17.08.2029 Reference no.: 4247 Explore and teach
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-electron Schrödinger equation for fermions and bosons with high accuracy and on the application of these methods to problems in the physics of oxides, semiconductors and their surfaces. Machine learning
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. Ready to be part of our team? Let’s shape the future together! About the team: The Computational Materials Discovery group is looking for a postdoctoral researcher working in the field of machine learning
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teach at the University of Vienna, where over 7,500 brilliant minds have found a unique balance of freedom and support. Join us if you’re passionate about groundbreaking international research and
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Theory and Machine Learning, can easily integrate into our team, independently contribute to current research, and work with responsibility for results. The research project is a collaboration between the
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52 Faculty of Chemistry Startdate: 01.06.2025 | Working hours: 40 | Collective bargaining agreement: §48 VwGr. B1 lit. b (postdoc) Limited until: permanent Reference no.: 3948 Explore and teach
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position from 01.10.2025 of a Postdoc Position at the Research Group Data Mining and Machine Learning at the Faculty of Computer Science, University of Vienna under the supervision of Prof. Claudia Plant
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simulations. Knowledge of behavioral and analytic methods related to representational similarity, multidimensional scaling, reinforcement learning, and fear conditioning is a plus. Experience developing and
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, Synthetic Data for Machine Learning in Privacy Research, Formalization of Security Risk Management, and Security and Privacy of Blockchain Technologies. In the long term, we are concerned with understanding
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Among the many good reasons to want to research and teach at the University of Vienna, there is one in particular, which has convinced around 7,500 academic staff members so far. They see themselves as