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September 18, 2025

**Job Description**
This PhD position focuses on the quantitative-empirical analysis of consumer and business behavior, investigating the impact of new technologies on this behavior, and the resulting implications for consumer welfare. The research is interdisciplinary, involving collaboration with the fields of Information Systems, Finance, and Psychology, and aims to create direct value for science, businesses, and policymakers through practice-oriented, data-driven analyses and innovative solutions.

**Skills & Abilities**
• Strong knowledge of quantitative methods, particularly in statistics and econometrics
• Experience in machine learning (a plus)
• Background in business/management/behavioral science
• Experience with programming languages such as Python or R
• Ability to conduct independent scientific research
• Experience working with large datasets (an advantage)
• Excellent communication skills in English (both written and spoken)
• Excellent organizational skills
• Proficiency in the German language (an advantage but not required)

**Qualifications**
Required Degree(s) in:
• Business/management
• Data science
• Psychology
• A related field

**Experience**
Other:
• Completed Master’s degree

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Experience
Other: • Completed Master's degree
Work Level
Ph.D
Employment Type
Scholarship
Salary
Position Classification: Pay group 13 (TV-L) Benefits: • A highly interdisciplinary research unit • Opportunity to conduct innovative research in marketing analytics • Access to state-of-the-art facilities, including virtual and augmented reality equipment, eye-tracking and facial expression analysis tools, and ECG and electrodermal activity measurement • Participation in international conferences • A vibrant international scientific network • A diverse and inclusive working environment • Extensive training opportunities
Valid Until
October 15, 2025
Details
Full-time / Part-time Duration: 36 months Brief location description if available, e.g., Campus-based: Campus-based
School / Department / Center / Lab
• Chair of Marketing Analytics • Heilbronn Data Science Center • TUM School of Management
Supervisor(s)
Ms. Elke Kröber
Supervisor Email
See Details
Technical University of Munich (TUM)
View profile

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