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empirical social research in sociology such as causal inference or machine learning or complex panel data analysis. We are seeking excellent applicants with an international research portfolio and network
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command of English, both spoken and written Knowledge of German (if not the native language), or the willingness to acquire German Ability to work in a team, strong organizational skills, reliability, and
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Materials Discovery group is looking for a postdoctoral researcher working in the field of machine learning of electronic structure and computational materials discovery. In this role you will be performing
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hitherto struggled with tackling such challenging systems. With the emergence of machine learning methods in the physical sciences, things are rapidly changing. This project is part of a large initiative
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struggled with tackling such challenging systems. With the emergence of machine learning methods in the physical sciences, things are rapidly changing. This project is part of a large initiative that aims
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geological field-based methods and big data applications and machine learning methods. Research focus will be on feedback processes between erosion, sedimentation, tectonics and climate, and topics could
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need expert knowledge in bioinformatic data analysis. Strong expertise in multi-omics data analysis (using R and Python) and a deep understanding of machine-learning models are must-criteria
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interest in Applied Mathematics, possesses solid and profound background knowledge in Numerical Analysis, Approximation Theory and Machine Learning, can easily integrate into our team, independently
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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. The Faculty of Computer Science
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| Classification CBA: §48 VwGr. B1 Grundstufe (praedoc) Limited contract until: 28.02.2026 Job ID: 4178 Among the many good reasons to want to research and teach at the University of Vienna, there is one in