ALTQNT Private Equity Flagship Track: Data Phase

Mandatory Kick-Off Date: 12/01/2026 (Note: This thesis starts with a mandatory kick-off event. For this reason, alternative starting dates cannot be accommodated.)

 

Overview

Our chair is engaged in a long-term effort to build one of Europe’s most detailed proprietary datasets on private markets. This initiative involves transforming unstructured transaction materials into structured, analysis-ready data. The project is conducted in collaboration with a data-driven alternative asset management firm and offers students a unique opportunity to work at the intersection of academic research and real-world investment practice.

Students participate in this initiative as part of a cohort-based process that has been refined over each cohort. Working in groups, they follow a clear and proven workflow for transforming GP reports into structured data, while benefiting from a strong support network and direct interaction with both academic researchers and industry practitioners.

Requirements

• A reliable and structured working style, with attention to detail.
• Basic proficiency in Excel and willingness to learn new tools.
• Motivation to contribute consistently within a collaborative project setting.

Structure & Timeline

1. Data Phase - 3 months part-time (in-person* at the chair, minimum 2 days per week)
   1. Kick-Off Day:
      • Meet-and-greet with supervisors, the chair, and representatives from our partner fund
      • Private Equity crash course based on TUM’s flagship PE module
      • Guest talk from the Head of Investments of our partner asset manager
      • Hands-on onboarding with our custom data entry systems
         
   2. Data Phase Support:
      • Multi-level support network: peer collaboration, guidance from experienced students, and direct access to PhD researchers and a postdoc
      • Weekly Q&A sessions to address challenges, monitor progress, and provide feedback
         
2. Research Phase - 3 months full-time (remote)
   1. Topic Selection:
      • Curated selection of pre-defined topics
      • Tailor-made individual research topics defined in collaboration with your supervisor - examples include
        • Deal structuring and value creation
        • Sponsor characteristics and investment outcomes
        • Distress and turnaround investing
        • Cross-sectional determinants of fund performance
           
   2. Bespoke supervision through our research team including:
      • Two Post-Doctoral Researchers

      • Two Research Associates

         

Notes
*We would love to offer hybrid or remote options - but the real-world data you’ll be working with is highly confidential and hence cannot leave our labs.