164 computational-physics-"https:"-"https:"-"https:"-"https:"-"INRAE" positions in Austria
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for a/an University assistant predoctoral 39 Faculty of Computer Science Startdate: 01.04.2026 | Working hours: 30 | Collective bargaining agreement: §48 VwGr. B1 Grundstufe (praedoc) Reference no.: 5431
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focuses on resource allocation among competing alternatives. Specifically, he studies how organizational features, such as the structure of the decision-making process and the composition of the decision
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. The second focuses on resource allocation among competing alternatives. Specifically, he studies how organizational features, such as the structure of the decision-making process and the composition
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assistant predoctoral 39 Faculty of Computer Science Job vacancy starting: 01.04.2026 | Working hours: 30.00 | Classification CBA: §48 VwGr. B1 Grundstufe (praedoc) Limited contract until: Job ID: 5431
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Computational Materials Physics. PhD students in the group acquire important transferable skills such as software development and project management. You will present your research at international and national
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research group Computational Materials Physics, and the Centre of Excellence on Materials for Energy Conversion and Storage (MECS CoE). PhD students in the group acquire important transferable skills such as
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stellar and planetary astrophysics and a strong background in computational astrophysics. The job consists of two equally important parts: 1) to contribute to the research in the area of atmospheric
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and interdisciplinary research group that provides a collaborative and supportive environment. Our team is member of the Vienna Doctoral School in Physics and the faculty research group Computational
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, international and interdisciplinary research group that provides a collaborative and supportive environment. Our team is a member of the Vienna Doctoral School in Physics, the faculty research group Computational
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, Bioinformatics, Computer Science, or similar Knowledge in bioinformatic analysis tools, Linux, Bash scripting and at least one of the following languages: Python, R Familiarity with plant transcriptomics