Contemporary information systems have become increasingly complex and heterogeneous in their (inter)dependencies and collaboration roles. At the code and implementation level, they commonly rely on third-party technology such as modules and libraries, whereas on the execution and operational level, they frequently outsource computation and storage to other parties such as cloud providers and service providers. On the business process level, they rely on partner services within a broader ecosystem to accomplish their overall goals, and on the data level, and in their use of artificial intelligence (AI) and Machine Learning (ML), they use consolidated data sets for training and optimization, and deploy pre-trained models obtained from third parties.

While this extensive degree of collaboration and reuse is key to the effectiveness and innovation capability of these systems, they also create substantial risk for misuse, cyber security and privacy issues. Software packages frequently become outdated or suffer from known vulnerabilities. Cloud providers may fail or suffer from significant data breaches, and AI models obtained elsewhere may come with specific backdoors, while data sets may be poisoned or unlawful (e.g., against data protection regulations such as GDPR).

You will incept and develop novel model-driven approaches to express complex supply chains and to subject them to risk analysis. You will evaluate the ensuing solutions in realistic application scenarios.

The ideal candidate will comply with following requirements:

• Master in Business and Information Systems Engineering, Business Engineering or Business Economics, or a master degree in information technology or science, computer science, informatics, or related fields.
• Strong affinity for the design and architecture of software- and information-intensive systems and supporting technologies.
• Good communication skills, particularly with regard to reporting, presentation and team work
• Able to work independently as well as in teams in an interdisciplinary context.
• Excellent English communication and interpersonal skills, both verbal and written.