157 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "University of Waterloo" positions at University of Vienna
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be given to female candidates. University of Vienna. Space for personalities. Since 1365. Data protection Application deadline: 10.12.2025 Reference no.: 4898 Tenure Track Professorships https
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is part of the Faculty of Earth Sciences, Geography and Astronomy at the University of Vienna. The research group “Data science in Astrophysics & Cosmology” is looking for three highly motivated and
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. The employment duration is six years from the start date. For more information about our research focus and team, please visit our homepage: https://mathematik.univie.ac.at/forschung/biomathematik-dynamische
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facilitate active scientific exchange and foster a good atmosphere, and therefore play a big role in our team. Learn more about us here: https://swa.cs.univie.ac.at/ Your future tasks: You actively participate
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Anthropology at the Faculty of Life Sciences seeks to appoint a pre-doctoral researcher with expertise in archaeology/archaeological science and to work with Associate Professor Katerina Douka (https
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administration Your profile: Master's degree in Computer Science, Business Informatics, Information Systems, Data Science, Math or an equivalent qualification with excellent grades An excellent command of English
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the project: https://www.anthrofuture.com . The employment duration is 3 years (36 months). Initially limited to 1.5 years, the employment relationship is automatically extended to 3 years
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in the field of Discrete mathematics. You can find more information about our research area and our team on our website: https://mathematik.univie.ac.at/en/research/arithmetics-algebra-and-discrete
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: https://koreanologie.univie.ac.at/ Your future tasks: You actively participate in research, teaching & administration, which means: Developing a doctoral research project in the area of Korean Studies
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: 30,00 | Classification CBA: §48 VwGr. B1 Grundstufe (praedoc) Limited contract until: 30.04.2029 Job ID: 5311 The work group Machine Learning with Graphs of the subunit Data Mining and Machine