Ulrike Morgalla, M.Sc.
Doctoral Student and Junior Research Fellow
Innovation and Entrepreneurship Research
Net Zero Lab
+49 89 24246-580
ulrike.morgalla(at)ip.mpg.de
Visit the Net Zero Lab:
Areas of Interest:
Environmental and Resource Economics, Energy Economics, Economics of Innovation, Market Design
Academic Résumé
Since 05/2024
Junior Research Fellow at the Net Zero Lab (Max Planck Institute for Innovation and Competition)
Since 10/2023
Doctoral Student and Junior Research Fellow at the Max Planck Institute for Innovation and Competition (Innovation and Entrepreneurship Research) and at the Munich Graduate School of Economics, LMU Munich
07/2023
Summer School, Barcelona School of Economics (BSE)
09/2022 - 07/2023
Master of Science (M.Sc.) in Economics, London School of Economics
01/2021 - 05/2021
Exchange Semester, University of St Andrews, UK
09/2018 - 11/2021
Bachelor of Science (B.Sc.) in Economics, University of Mannheim
Work Experience
04/2022 - 07/2022
Internship, next economy lab, Bonn
01/2022 - 02/2022
Internship, ifo Center for Energy, Climate and Resources, ifo Institute, Munich
10/2019 - 12/2020 and 06/2021 – 11/2021
Student Research Assistant in Market Design, Leibniz Centre for European Economic Research (ZEW), Mannheim
Publications
(2025). Who Uses AI in Research, and for What? Large-scale Survey Evidence from Germany, Max Planck Institute for Innovation & Competition Research Paper, No. 25-11.
- The integration of AI into scientific work holds significant potential to accelerate innovation. We surveyed researchers in two leading German research organizations to examine AI adoption, barriers, and perceived impact on research. Researchers are widely using AI tools-often for primary and creative tasks-and many expect the technology to be transformative for research. Effective use, however, requires training, both through hands-on experience and dedicated learning resources. A persistent gender gap in AI use can largely be explained by differences in familiarity, pointing to a clear opportunity for organizational intervention. Legal uncertainty and privacy concerns also emerge as major barriers, with researchers calling for clear, high-level regulatory guidance. Overall, our findings underscore the importance of institutional action to support equitable and effective AI adoption in research.
- Available at SSRN