ETH Zurich is one of the world's leading universities specializing in science and technology. It is renowned for its excellent education, its cutting-edge fundamental research and its efforts to put new knowledge and innovations directly into practice. The Chair of Strategic Management and Innovation (SMI) shares a common vision of contributing significantly to the highest level academic research in the fields of strategic management and innovation, directing our work to topics such as knowledge management, information systems innovation, collaborative innovation, organization and management theory, and competitive strategy. We offer an inspiring, supportive, and team-based research environment to support your immediate immersion into an ambitious research agenda.
PhD Position: Organizing in the Age of Artificial Intelligence (100%)
Recent advancements in Artificial Intelligence (AI) have brought algorithms capable of undertaking tasks that previously required human judgement and decision making. This project aims to advance understanding of how fast, accurate, and low-cost predictions provided by AI can be better integrated into organizational functions to enhance productivity, reduce coordination costs, and improve knowledge sharing within organizations. These questions are of particular relevance due to the unique characteristics of AI algorithms including their opaqueness, embedded biases, and autonomous nature. These characteristics make it difficult to garner trust and perceived fairness among individual users and organizations. The PhD candidate will investigate various aspects of AI applications in organizations that have been shown to be of critical importance yet remain underexplored. The PhD candidate will be co-supervised by Prof. Georg von Krogh and a team of senior researchers at SMI (www.smi.ethz.ch/group-people). The duration of this position is three to four years, the gross salary will be in accordance with the regulations of ETH Zurich.
The prospective candidate should have a MSc, MA, or MPhil degree (MBAs are not eligible) in business administration or related fields such as computer science, psychology, sociology, mathematics, engineering, physics, or statistics. The applicant should have a strong affinity with information technology and ideally be experienced with field research and have some background in machine learning and statistics. The applicant must have excellent written as well as spoken English.