The Ruhr area, one of Europe‘s largest metropolitan regions, offers attractive career opportunities for excellent scientists and scholars from around the world. In 2021, Ruhr-Universität Bochum, TU Dortmund University and the University of Duisburg-Essen established the Research Alliance Ruhr to bundle their cutting edge international research on the most urgent challenges facing humankind. There will be four research centers and a college. This is just the latest chapter in our long-standing collaboration as the University Alliance Ruhr (UA Ruhr), a community of 14,000 researchers and 120.000 students in the heart of Germany.
The person selected to hold the new professorship for Fairness and Transparency will specialize in research and teaching in the field of Trustworthy Machine Learning, FAccT, Privacy Law & Data Science, Ethics and Artificial Intelligence, and Human-AI Decision Making. The teaching load is reduced to four weekly hours per semester. The successful candidate is expected to contribute to English-taught courses either in RUB’s computer science or dedicated IT security study programs.
The Center will enable research that connects computer science, cybersecurity & privacy, and society in order to increase trust in the digital world. Thus, we particularly welcome applications with a strong interest in interdisciplinary research. An ideal candidate will have publications in both technical outlets but also in areas such as law, psychology, sociology, economics or other humanities. Applicants should have an excellent track record in research in at least one of the following areas:
- Trustworthy Machine Learning for Privacy & Security
- FAccT (Fairness, Accountability, Transparency)
- Technology Policy, Privacy Law & Data Science
- Ethics & AI
- Human-AI Collaborative Decision Making
Computer Science and be willing to contribute to interdisciplinary collaborative research projects and collaborations within and outside the RC Trust and the Universities of the Research Alliance Ruhr. Prerequisites for the position are excellent scientific qualifications, usually demonstrated by a doctorate of outstanding quality, positive evaluation as a junior professor, habilitation or equivalent academic achievement, top international publications, as well as proof of suitability for academic teaching. Strong social and leadership skills and willingness to participate in academic self-administration complete your profile.
In the case of the W2 professorship with W3 tenure track, the successful candidate will initially be appointed as a temporary civil servant for five years. At the end of this five-year period at the latest, the tenure track will lead to continued employment as a tenured W3 university professor, provided that the necessary aptitude, competence and academic performance have been demonstrated and that the legal requirements pertaining to Section 38 of the North Rhine-Westphalia Higher Education Act (HG NRW, Gesetz über die Hochschulen des Landes Nordrhein-Westfalen) are met. In addition, the recruitment criteria of Sections 36 and 37 of the North Rhine-Westphalia Higher Education Act (Gesetz über die Hochschulen des Landes Nordrhein-Westfalen, HG NRW) apply.
If you are interested in the position, please send your application in a single PDF file by July 29, 2022 to: career(at)casa.rub.de. Please provide the usual documents:
- list of publications
- documents demonstrating your academic and professional career, including copies of certificates
- an exposé of your research profile with reference to its relevance for the Research Center
- a list of successful external grant applications
- an overview of your experience in academic self-administration
- a teaching-learning concept including information on your previous teaching activities.
Questions will be answered by Prof. Christof Paar, e-mail: career(at)casa.rub.de
Further information about the Faculty of Computer Science: https://informatik.rub.de/en/
The official job add can be found here.
Information on the collection of personal data at the application process: