We are looking for curious researchers who are excited to combine theoretical depth with real-world relevance and contribute to understanding the future of intelligent sociotechnical systems.

Be part of innovative research exploring the evolving role of AI and digital platforms in shaping the future of business.

This PhD position lies at the intersection of Generative and Agentic AI, digital platforms and platform ecosystems, and digital transformation in incumbent firms, making it suitable for candidates interested in either academic or industry careers. It offers the opportunity to join our research group in studying how Generative and Agentic AI shape the future of information systems and digital platforms, how these AI paradigms require architectural and governance adaptations in traditional systems and platforms, how AI paradigms and platform-based business models define new trajectories of digital transformation in incumbent firms, and how the combination of human and machine agency reshapes organizational routines and knowledge management.

With publications in top-tier journals and conferences, our research group is experienced in combining qualitative and computational approaches, including simulation and agent-based modeling, to study complex sociotechnical systems. We work closely with industry partners and develop empirically grounded theories from real-world phenomena. The PhD candidate will have the opportunity to contribute to cutting-edge research projects, collaborate with international scholars and practitioners, and publish in leading Information Systems journals and conferences.

Your tasks

• Conduct research on topics related to Generative and Agentic AI, digital platforms and platform ecosystems, and AI- and platform-induced digital transformation

• Conduct qualitative and quantitative research, particularly interviews, agent-based modelling, and simulation studies

• Perform independent project work in research areas of high theoretical and practical relevance

• Publish in leading conferences and contribute to publications in top-tier journals

• Support teaching activities and executive education programs

We offer

• A high degree of freedom combined with intensive and continuous support for research and publications throughout all stages of the PhD journey

• Engagement with state-of-the-art topics in both research and teaching, in collaboration with international scholars, top-ranked business schools, and industry partners

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  A highly dynamic, motivated, and supportive team environment

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  Attractive working conditions, including flexibility and competitive salary

  Participation in international conferences

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  Support for post-graduation career development

Your profile

• Master's degree with a grade average of at least 5.0 (equivalent to 2.0 in Germany and Austria) in Information Systems, Business Informatics, Computer Science, Business Administration (Management), or similar fields
• Knowledge of qualitative (e.g., case study research) and quantitative methods. Programming skills, particularly in Python, are required. Experience with simulation-based research is considered a strong asset
• Excellent command of written and spoken English. Strong academic writing and presentation skills in English are required. German fluency is considered a strong asset
• Strong analytical and conceptual capabilities, as well as a structured, independent, and proactive working style
• Ideally, some initial experience in scientific writing, research projects, or relevant professional experience

The PhD candidate will be affiliated with the Institute of Information Systems and Digital Business (IWI-HSG), one of the largest institutes at the University of St. Gallen. At IWI-HSG, we have been researching business models and the application of digital technologies for more than 30 years. The main research theme of Prof. Dr. Kazem Haki’s group is complex sociotechnical systems. Currently, the group conducts research in three areas related to this theme: digital platforms and platform ecosystems, Generative and Agentic AI, and computationally intensive theory construction.