181 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" positions at University of Vienna
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administration and organisation. We are looking for a/an University assistant predoctoral/PhD Candidate Optical Quantum Computing and Machine Learning 51 Faculty of Physics Job vacancy starting: 01.02.2026 (MM-DD
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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
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the PhD should be within the areas of expertice of the laboratory for Cognitive Research in Art History (https://crea.univie.ac.at/). Your future tasks: PhD thesis, preferably in the area of the FWF
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these areas of demography, we particularly welcome outstanding applicants whose research addresses migration and its interrelations with human capital formation. Applicants should be able to teach all the main
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professorship will be affiliated with the Faculty of Physics at the University of Vienna and integrated into the Gravitational Physics group (https://gravity.univie.ac.at/ ), an active research unit engaged in
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University of Economics and Business, and with the BOKU University. https://ie.univie.ac.at/en/ Your academic profile: Doctoral degree/PhD Two years of international research experience during or after
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PhD should be within the areas of expertice of the laboratory for Cognitive Research in Art History (https://crea.univie.ac.at/). Your future tasks: PhD thesis, preferably in the area of the FWF project
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University assistant (prae doc) as soon as possible, at the Research Group Data Mining and Machine Learning at the Faculty of Computer Science under the supervision of Univ.-Prof. Dipl.-Inform.Univ. Dr
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, radionuclides, or air pollutants. Our future research strategy also includes studies of the higher atmosphere. To learn more about our team, we invite you to visit our website: https://flexteam.univie.ac.at
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for learning new methodological skills required for the project. A successful applicant will have a MSc degree in microbiology or ecology with a focus on microbial ecology, or a related discipline