The Jheronimus Academy of Data Science (JADS), the joint Data Science Academy of Tilburg University and Eindhoven University of Technology, the Netherlands, invites applications for an Assistant Professor position in Data-Driven Business/Entrepreneurship. We welcome applications from individuals with research interests and high-quality track record on the interface of data science/AI and strategy/entrepreneurship/innovation management. Prior experience and interest in natural language processing and text mining techniques is appreciated.
The assistant professor will be invited to join the externally funded research projects such as designing innovative business models for a European platform in healthcare and new ventures that employ data science and AI for new services. The assistant professor is expected to teach at both the bachelor’s
and the master’s level in such courses as Strategy and Business Models, Data-Driven Businesses, and Statistics for Data Scientists. Teaching at the PDEng, PhD and Executive levels, supervising master thesis projects as well as PhD projects is also part of the expected responsibilities. Teaching/research time is divided roughly 50/50.
The faculty at JADS publishes in various top journals and conferences in line with their scientific discipline. For the Data Entrepreneurship unit such journals include Strategic Management Journal, Academy of Management Journal, Journal of Business Venturing, Entrepreneurship Theory and Practice, Journal of Product Innovation Management, and Small Business Economics, Journal of Information Technology, Decision Support Systems, etc. Due to the strong ecosystem and funding acquisition track record, JADS can uniquely facilitate initiation of new projects in collaboration with various organizations, and the new colleague will be expected to join such initiatives.
Data Entrepreneurship unit @ JADS
There are three research units in JADS: Data Governance, Data Analytics, and Data Entrepreneurship. The Data Entrepreneurship (DE) unit focuses on how data can be used to create and capture value for business and society. We combine the two fields, Data Science and Entrepreneurship/Business. The main research lines are:
(1) investigating how and why big data and AI enable established businesses and entrepreneurs to become successful. In particular, the unit studies the implications of big data and AI on the digital value propositions, business models, platforms, and strategies of firms, and analyzes the (new) ways in which value can be captured from to digitalization. Example projects: Digital disruption and new business models that arise with digitization and transition to it; new business opportunities due to data; best ways to design and scale up platforms.
(2) applying and developing state-of-the-art data science methods and techniques to better address strategy/management/entrepreneurship research questions. Example projects: Using computer vision to analyze emotions and body language to infer the best pitching strategies of entrepreneurs to VCs; using natural language processing to understand optimal competitive positioning in different markets; using network analysis to understand and predict interaction dynamics in organizations.
(3) augmenting data science techniques with data-driven decision-making tools on the interface between human cognition and business and innovation. Example projects: Recommender systems that encourage getting “outside of the news bubble” and explainable AI; how users react to privacy-sensitive permissions in the Google Play Store, in particular excessive permissions that are not needed for the app functionalities.
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