About the Module

What students say about TUM-DI-LAB!
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How to apply:

TUM and Erasmus master students are invited to apply for the development of one or more of the proposed projects. According to staff capacity, projects, student applications and qualifications, groups (preferably from different backgrounds: Mathematics, Computer Science, Biology, Engineering, Medicine, etc.) will be formed to work on assigned projects. You can also apply in group for a specific project. If you apply in group, every student must send an application separately and mention the names of the other students that are part of the group.

For applying, submit the following documents as a single pdf file to di-lab@ma.tum.de 

  • First: Check if your master program accepts TUM-DI-LAB!
  • Brief Curriculum Vitae (mention programming skills, e.g. R, Python, Java, C++, etc.)
  • Transcripts, if you are in 1st semester of Master then add the transcripts of Bachelor program.
  • Topic of Bachelor Thesis
  • One paragraph per project, half a page, about how you can contribute to the chosen project(s)
  • If you apply to more than one project please rank them in order of relevance to you
  • If you apply in group, please mention the name of the other group members in your application
  • programming_and_software_skills_assessment.pdf (see more information below)
  • Mention if you will be able to attend the 4 workshops at LRZ mentioned below

Please consider that if you are accepted to one of the projects then you can not apply again to TUM-DI-LAB in future semesters. If you are not selected to any project we encourage you to apply again in future semesters. 

Important notice:

The LRZ offers training on supercomputing (with R and Python) and deep learning for students accepted to TUM-DI-LAB projects, see below for the dates and topics. Students accepted to TUM-DI-LAB will need to register (once the student is accepted) and attend the following courses at LRZ:

  • Monday, October 08, 2018, 9:00-18:00: Introduction to the LRZ Supercomputing & Machine Learning Infrastructure.
  • Tuesday, October 09, 2018, 9:00-13:00. Using R at LRZ
  • Tuesday, October 09, 2018, 14:00-18:00. Using Python at LRZ.
  • Optional course: Tuesday, November 27. Machine Learning with R at LRZ