How to apply:
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 firstname.lastname@example.org
- First: Check if your master program accepts TUM-DI-LAB!
- Submit the following documents as a SINGLE PDF file (Maximum 2 MB File):
- Brief Curriculum Vitae (Telephone number, Nationality and Gender). 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, at most 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
- Mention if you will be able to attend the LRZ workshops 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.
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 7th
- 9:00 AM to 12:30 PM: Introduction to GNU/Linux and the shell
- 1:30 PM to 5:00 PM: Introduction to working on remote systems with SSH
- Tuesday, October 8th
- 9:00 AM to 12:30 PM: Introduction to the LRZ HPC Infrastructure
- 1:30 PM to 5:00 PM: Introduction to the LRZ Compute Cloud
- Wednesday October 9th
- 9:00 AM to 12:30 PM: Using Python at LRZ
- 1:30 PM to 5:00 PM: Using R at LRZ
- Thursday, October 10th
- 9:00 AM to 12:30 PM: Enhance Machine Learning Performance with Intel® Software tools
- 1:30 PM to 5:00 PM: Deep Learning at Scale using Distributed Frameworks
- Friday, October 11th
- 9:00 AM to 12:30 PM: Advanced HPC cluster usage with R
- 1:30 PM to 5:00 PM: Machine Learning/Deep Learning with R at LRZ