Scientific Staff
vor 2 Wochen
This advertised position is funded by the FFG as part of the project GNNRecSys: Geometric deep learning based recommender engine with implicit feedback data. You will work on the development of new techniques for graph-based recommender engines based on graph neural networks (GNNs). This includes the development of new methods, e.g., GNNs for heterogeneous graphs and scalable GNNs, as well as the practical implementation and experimental evaluation.
We offer a wide range of professional and personal development opportunities, early assumption of responsibility in research projects, and international exchange.
The position will be limited to 15 months and is to be filled as soon as possible. The employment is over 40h/week.
Participation in research and administration:
- Participation in research projects / research studies
- Participation in publications / academic articles / presentations
- Participation in teaching and supervision of students (optional)
- Involvement in the organisation of meetings, conferences, symposiums
- Involvement in the department administration as well as in teaching and research administration Participation in research and administration:
- Participation in research projects / research studies
- Participation in publications / academic articles / presentations
- Participation in teaching and supervision of students (optional)
- Involvement in the organisation of meetings, conferences, symposiums
- Involvement in the department administration as well as in teaching and research administration
**Benefits**:
Eligibility criteria
- Excellent basic knowledge of Machine Learning and Data Mining
- Strong programming skills
- Demonstrable interest in scientific work and in publishing activities
- PhD or Doctoral degree in computer science / mathematics or comparable studies
- Excellent command of written and spoken English
- Team player with strong social skills
- Ability to work independently and reliably
Selection process
- Excellent basic knowledge of Machine Learning and Data Mining
- Strong programming skills
- Demonstrable interest in scientific work and in publishing activities
- PhD or Doctoral degree in computer science / mathematics or comparable studies
- Excellent command of written and spoken English
- Team player with strong social skills
- Ability to work independently and reliably
Additional comments
The University of Vienna was founded in 1365 and is the oldest university in the German-speaking world and one of the largest in Central Europe. At present, about 88,000 students are enrolled in 180 courses at the University of Vienna. The University of Vienna is also the largest teaching and research institution in Austria with 8,900 employees, 6,700 of whom are scientists and academics.
Web site for additional job details
Required Research Experiences
**RESEARCH FIELD**
Computer science › Autonomic computing
**YEARS OF RESEARCH EXPERIENCE**
None
Offer Requirements
Skills/Qualifications
- Excellent basic knowledge of Machine Learning and Data Mining
- Strong programming skills
- Demonstrable interest in scientific work and in publishing activities
- PhD or Doctoral degree in computer science / mathematics or comparable studies
- Excellent command of written and spoken English
- Team player with strong social skills
- Ability to work independently and reliably
Desirable qualifications are:
- Solid knowledge and interest in at least one of the following: Graph Neural Networks, Recommender Engines
- Experience with PyTorch Geometric
- Practical experience in the realization of industrial projects
Specific Requirements
- Excellent basic knowledge of Machine Learning and Data Mining
- Strong programming skills
- Demonstrable interest in scientific work and in publishing activities
- PhD or Doctoral degree in computer science / mathematics or comparable studies
- Excellent command of written and spoken English
- Team player with strong social skills
- Ability to work independently and reliably
Desirable qualifications are:
- Solid knowledge and interest in at least one of the following: Graph Neural Networks, Recommender Engines
- Experience with PyTorch Geometric
- Practical experience in the realization of industrial projects
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