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Technical University of Munich

 

The TUM Data Innovation Lab (TUM-DI-LAB) brings master’s students together with industry and research partners to work on real‑world, data‑driven AI challenges in a structured academic setting. Student teams collaborate over 15 weeks during the TUM winter or summer lecture period on open problems proposed by external partners, actively designing, developing, and evaluating AI models, prototypes, and analytical tools — gaining hands‑on development experience while partners explore analyses and early solution concepts supported by TUM.

Our Offer for Students:

  • Up to 10 ECTS credits, depending on the degree program.
  • Work on real AI projects in interdisciplinary teams.
  • Gain hands‑on experience beyond coursework.
  • Academic supervision by TUM researchers and industry experts.

The team typically delivers working prototypes, evaluated AI models, and structured analytical results in the form of a final report, which are presented and discussed in an academic context.

Interested as a student?
Apply to participate in upcoming TUM‑DI‑LAB projects.

Our Offer for Industry and Research Partners:

  • Collaborate with highly qualified master’s students.
  • Explore early‑stage, data‑ and AI‑driven challenges.
  • A student team contributes up to 1,500 working hours per project.
  • Meaningful outcomes: Partners receive analyses, prototypes, or early solution concepts that can serve as input for further internal development.

Interested in collaborating?
Learn more about how to propose a challenge and collaborate with the TUM‑DI‑LAB.

How the TUM‑DI‑LAB Works:

  • Project definition: Partners propose AI‑ or data‑driven challenges.
  • Team formation: Interdisciplinary teams of 4-5 master’s students are formed.
  • Project phase: Over 15 weeks (winter or summer semester), teams iteratively develop and evaluate models, prototypes, or analytical concepts.
  • Supervision: Teams receive continuous methodological support from TUM researchers and partner experts.
  • Final presentation: Project results are presented to partners and TUM supervisors.

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