158 computer-science-programming-languages-"Prof"-"Fraunhofer-Gesellschaft"-"Prof" positions at University of Vienna in Austria
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expect: • Completed doctoral/PhD thesis in history or another cultural or social science subject with a focus on the 20th and 21st centuries • Teamwork skills • Experience in independent teaching
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Discovery, Chemistry, Biochemistry, Biotechnology, Microbiology), completed doctoral study in Science. Computer literacy (MS office, management of databases). Very good command of oral and written language
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join our accomplished team! Your personal sphere of influence: The Doctoral School Computer Science DoCS (https://docs.univie.ac.at) founded in 2020 offers a structured doctoral programme that supports
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Data Stewardship program. The Faculty of Earth Sciences, Geography and Astronomy (Fakultät für Geowissenschaften, Geographie und Astronomie / FGGA) is therefore looking for a highly motivated person (m/f
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-led museums studies within the art history program. Your responsibilities include: developing and leading a dynamic research agenda in museum studies; designing and teaching courses inter alia in museum
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and determination? We are currently seeking a/an University Assistant postdoctoral - Researchgroup VDA 39 Faculty of Computer Science Job vacancy starting: 15.10.2025 (MM-DD-YYYY) | Working hours
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Scientific Computing focuses on research in programming paradigms, languages, compilers, and software and hardware infrastructures for scientific computing to support users in the process of solving
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research activities in the field of applied and computational PDEs in a coherent manner. Current research covers a wide range of applications, including biology, materials science, and astrophysics, and uses
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Communication”, Master’s programme “Translation” and Master’s programme “Multilingual Technologies”, with 14 languages and currently 2000 students. Your future tasks: You hold courses on BA and MA level You
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to the department Ph.D. program and will work on the development and analysis of statistical methods for machine learning, particularly in the context of high-dimensional models and with a particular focus on methods