Sort by
Refine Your Search
-
Category
-
Program
-
Employer
- Universität Wien
- University of Innsbruck
- AIT Austrian Institute of Technology
- Johannes Kepler University
- Graz University of Technology
- Medical University of Innsbruck
- Austrian Academy of Sciences, The Acoustics Research Institute (ARI)
- CeMM - Research Center for Molecular Medicine of the Austrian Academy of Sciences
- Personalabteilung der Montanuniversität Leoben
- Polymer Competence Center Leoben GmbH
- ;
- AIT Austrian Institute of Technology GmbH
- Austrian Academy of Sciences, The Human Resource Department
- Austrian Academy of Sciences,The Space Research Institute (IWF)
- Danube Private University
- Karl-Franzens-University Graz
- Klagenfurt University
- Medical University Innsbruck
- Medical University of Vienna
- TU Wien
- University of Graz
- University of Natural Resources and Life Sciences Vienna
- Veterinärmedizinische Universität Wien (University of Veterinary Medicine Vienna)
- Vienna University of Technology
- 14 more »
- « less
-
Field
-
on research projects, publications, initiatives and events organised by the department. You will be involved in the organisation of conferences. You will teach courses independently from the 2nd year of
-
able to teach in German within three years from the signing of the contract Advanced computer skills are desirable. Ability to work in a team. Organisational skills. Additional Information Benefits What
-
to research and teach at the University of Vienna, there is one in particular, which has convinced around 7,500 academic staff members so far. They see themselves as personalities who need space for
-
| Collective bargaining agreement: §48 VwGr. B1 Grundstufe (praedoc) Limited until: 31.05.2028 Reference no.: 2196 Among the many good reasons to want to research and teach at the University of Vienna, there is
-
: Good German speaking and writing performance. Sound basic knowledge in the area of mechanical properties of materials. Basic knowledge of fracture mechanics, materials testing and machine learning
-
disciplines relevant for the position. Outstanding scientific qualification and relevant doctorate in the field of high-voltage engineering Experience in the application of machine learning in power engineering
-
research projects of the institute, in particular, in the development, evaluation, and practical application of machine learning methods (especially deep learning) Publication of scientific results in
-
aided design preferred Communication skills in German and English for interaction an an international work environment (CEFR level English at least B2; in case German skill level is below B2, English
-
curriculum (AI, Machine Learning & Pattern Classification, Probabilistic Models) Independent and collaborative research in the fields of computational (audio) perception and Music Information Research (MIR
-
production Use of new and future digital tools in the field of materials research (AI/machine learning, digital twinning of material development and manufacturing processes) "High-throughput processing