The Chair for Innovation Management (Prof. Dr. Oliver Gassmann) at the Institute of Technology Management conducts research on the strategic management of innovation, business model innovation, and the management of emerging technologies like artificial intelligence and machine learning (AI/ML). We are looking for a research associate/PhD candidate. This position is intended to assist in researching the future of work and understanding the impact of AI/ML on people and organizations. The candidate will be part of our team working on topics at the intersection of technology and innovation management, strategic management, and artificial intelligence.
The main tasks of this position consist of assisting in research, teaching support, and impact projects. In addition, candidates for this position are expected to enroll in the PhD program at the University of St. Gallen. This position will offer candidates an excellent chance to improve their analytical skills as well as acquire deep insights into the central management challenges and opportunities posed by artificial intelligence.
- Master's degree from a recognized university in economic or social sciences, or in a discipline related to those taught at the University of St. Gallen's School of Management
- Excellent academic record: Your grade point average must be at least 5.00 (not rounded) in the Swiss grading system
- Candidates should have a strong background in management and innovation and display a keen interest in artificial intelligence/machine learning
- Command of qualitative and/or quantitative research methods
- Analytical thinker and self-starter who takes ownership of and can manage multiple projects simultaneously
- Steadfast and ambitious team player with desire to continuously develop both personally and professionally
- Excellent written and oral communication skills in English and German
- Work and research experience in related fields beneficial
The position will remain open until filled. The starting date for the position is negotiable but starting as soon as possible is preferred.
Interested candidates should apply online by submitting their application (cover letter describing your motivation and research competence, curriculum vitae, grade transcripts, letter(s) of recommendation, and a writing sample).