Machine Learning Lab

Possible Topics

Here, we collect possible topics for BSc/MSc projects or theses. Please note that the list of projects below is often incomplete, since we always have new ideas as time goes by and we do not always update the list right away.

Getting in Touch about Theses

Since machine learning is currently one of the hottest topics around, our small group is flooded with requests, and we may not be able to offer projects to every interested student. Generally, it helps for finding a matching project if you have taken and excelled at our courses. All projects in our research group should be carried out in teams of at least 2 students (max. 4). Theses can also be done in synergy with theses/projects by others, but each student has to write their thesis by themselves, appropriately acknowledging work done by others. We strongly recommend doing a MSc project with our group before inquiring about a MSc thesis.

Please see Theses in Industry below to see in which cases and how it is possible to do one.

Projects: Expected Time Frame and Outcome

The faculty does not set a hard deadline for projects as they do for theses (i.e., 6 months). However, to avoid projects running too long, our chair has decided to limit them to a maximum of 3 months of full-time work or 6 months of half-time work (deviations are possible, but should be agreed upon beforehand). The goal of a project group is to produce a short, yet high-quality research that equals work at top machine learning conference workshop, such as NeurIPS, ICML, or ICLR.

Requirements for Reproducible Experiments

When doing a project or thesis in our group, we put high value on reproducibility. This means that someone unfamiliar with your code can understand and reproduce what you have done, not only now, but also in the far future. In your final presentation, you will need to describe the steps you took to ensure reproducibility and this will affect your final grade. This minimally entails that all code you used must be made available and depending on the project, your supervisor may require you to containerize your code (e.g., Singularity). We strongly recommend you think about reproducibility at the very start of the project and not just before handing it in.

Teaching Assistant [Only MSc]

We teach every semester and always look for helping hands in organization and teaching. See here for courses we usually teach. We explain in more detail in the application form.

Research Assistant (HiWi) [MSc and BSc]

We are always looking for talented students to assist us in our research. If you can quickly code algorithms from papers and repeat their experiments, we want you! As a research assistant (in German, "Hilfswissenschaftler", in short, HiWi), you would work on a research project supervised by one of our PhDs or PostDocs. 

Please see here for currently open research projects looking for a HiWi. 

Alternatively, feel free to fill out this form to express your general interest in a HiWi position at this lab (ideally, with at least two projects you might want to work on as points of reference).

Note: a HiWi position is only available to students enrolled at the University of Freiburg

If you are currently doing a postdoc or PhD in a field very closely related to our group’s research and would like to visit our group, please follow the procedure described on the open positions page.

If you do not have a MSc degree, there is no possibility for doing an internship with us. Rather, we encourage you to apply to our MSc programme. Information on this programme and how to apply can be found here: https://www.tf.uni-freiburg.de/en/study-programs/computer-science/m-sc-computer-science. We note that in the AI masters program you can basically fill your entire curriculum with AI courses.

DAAD Wise program: We do not accept applications for DAAD internships anymore.

We only supervise MSc theses in industry in the following exceptional circumstances:

• 1. The research topic is directly related to AutoML and discussed with us before the research starts.
• 2. The industry partner promises that all code (including scripts to run experiments, baselines, etc) you develop will be open source and freely available to the academic community
• 3. The industry partner promises that at least part of the evaluation is on publicly available data and therefore directly reproducible by the academic community
• 4. The industry partner promises that the results will be freely publishable and that there is no NDA we have to sign
• 5. The deliverables include the open-source code (2.) and a Docker or Singularity container that reproduces the results of the thesis on freely available data (3).

The promises referred to above are to be made in writing.