Ruhr-Uni-Bochum

Open Position: W2-Tenure-Track-Professorship for Human Factors in Security and Privacy

A W2-Tenure-Track-Professorship for Human Factors in Security and Privacy is to be filled at the Faculty of Computer Science of Ruhr-Universität Bochum at the earliest possible date.

Copyright: RUB

Description

Applicants should have an excellent track record in research and teaching in at least one of the following areas:

  • Human aspects affecting the design, implementation, and use of cryptography
  • Planning and conduct of empirical studies with end-users, security experts, and software developers, investigating topics such as usable authentication, mobile security, secure messaging
  • Application of qualitative and quantitative methods in IT security research, and development of new methods.

Applicants must have published empirical research in these areas and have experience with research methods for laboratory, online and field studies with software developers and end-users. Experience in designing and conducting intervention studies to improve understanding and correct use of cryptography - evidenced through publications - is essential.

We are looking for a scientist with an internationally visible research profile (evidenced through collaborative publications, and membership of program committees of the relevant top-tier conferences IEEE S&P, USENIX, ACM-CCS NDSS, CHI and USENIX) who will complement existing research areas and actively participate in the development of the Faculty for Computer Science. We expect a willingness to cooperate with the Horst Görtz Institute for IT Security (a Research Department of Ruhr-Universität Bochum) and an active role in current and planned projects, especially in the Cluster of Excellence "CASA: Cyber Security in the Age of Large-Scale Adversaries". The Max Planck Institute for Cybersecurity and Privacy offers additional possibilities for collaboration.

The responsibilities of the future chair holder include participation in teaching in the IT security and computer science study programs. The prerequisites are excellent scientific qualifications, usually proven by a doctorate of outstanding quality, positive evaluation as a junior professor, habilitation or equivalent academic achievement, top international publications in top-tier publication venues for security and privacy research, as well as proof of special suitability for academic teaching. Also required is the willingness to participate in academic self-administration. 

Further information can be found on https://www.ruhr-uni-bochum.de/en/conditions-governing-tenure-track-professorships.

Furthermore, we expect:

  • strong commitment in teaching,
  • the willingness to engage in interdisciplinary scientific work,
  • the willingness and proven ability to submit third-party funded research projects or to participate in existing research collaborations,
  • a convincing strategy to establish a research area that extends existing research in the CASA project and the faculty of computer science.

At RUB, we are committed to promote the careers of women and people of color in the areas in which they are underrepresented. We therefore encourage and welcome relevant applications as well as those from non-binary or gender-queer applicants. Applications from persons with disabilities or equal status are very welcome. Ruhr-Universität Bochum is an equal opportunities employer. 

Applications with the usual documents (curriculum vitae, copies of certificates, list of publications, proof of particular suitability for academic teaching, details of research interests, list of own third-party funding), if possible in digital form, should be sent by 10.01.2022 to the Dean of the Faculty of Computer Science at Ruhr-Universität Bochum, Prof. Alexander May, e-mail: career@casa.rub.de.

Further information can be found on our homepages at
https://www.informatik.rub.de/en
https://casa.rub.de/en/

Information on the collection of personal data at the application process:
https://www.ruhr-uni-bochum.de/en/information-collection-personal-data-application-process 

General note: In case of using gender-assigning attributes we include all those who consider themselves in this gender regardless of their own biological sex.