University of Luxembourg is seeking candidates to fill a PhD studentship broadly in the research area of security, privacy and trust. Candidates should hold a master degree in computer science or mathematics.
This studentship will be conducted in the Security and Trust of Software Systems (SaToSS) group, led by Prof Sjouke Mauw, with co-supervision from an experienced researcher within the research group. The SaToSS group has a track record in producing outstanding researchers, for example the most recent PhD graduate, Jorge Toro-Pozo, received the award for the best thesis of the year in computer science at University of Luxembourg and is now a researcher at ETH Zurich.
PhD thesis topics are not limited to:
The methodology typically applied in the group is to harness (formal) methods and tools to analyse topical security and trust problems such as the above. Methods employed are not limited to various strands of symbolic analysis, concurrency theory, logic, graph theory, and game theory. A master degree in computer science with an security element helps; however a student comfortable proving theorems can generally convert to such topics, if research in security is a new. Specific topics can be provided on request, and can be matched to a strong student's background and interests.
The University of Luxembourg offer the following competitive postdoctoral research positions in the SaToSS group in the area of formal methods applied to security and privacy.
The university is an equal opportunities employer; we encourage applicants from groups that are in a minority in computer science (notably female candidates). Applications will be considered upon receipt, in order to fill positions as soon as possible.
This position is for a postdoctoral researcher who will contribute to the project “Spin and Bias in Language Analyzed in News and Text (SLANT)” which is jointly funded by the Fonds National de la Recherche (FNR) Luxembourg and Agence National de la Recherche (ANR) France, and will be carried out in collaboration with researchers at the University of Toulouse and INRIA Lille, France. The aim of the project is to characterize bias in textual data and automatically detect such bias using tools and techniques from NLP, Machine Learning, Linguistics, Logic and Game Theory.
Apply online here