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Technical University of Munich

Student research projects

​​​​​​​At MMK, almost all work can be done remotely, and in most cases, the processing of the work is not limited.

There are always topics for student research projects here at MMK (Bachelor's and Master's thesis, Research Internship, IDP).

When you have found a topic please contact the scientific assistant. If there is no suitable topic, please contact an assistant to get one.

Ingenieurpraxis: The aim of the Ingenieurpraxis is to have a look into the processes in the industry. For this reason we don't offer some Ingenieurpraxis here at MMK, but it is possible to supervise you if you find a position in a company.

Additionally, we do not offer any internships to students from outside TUM. Because of the volume of requests we receive, it is not possible for us to answer all emails with internship requests.

Current appointments of the MMK student research project talks

Topics for Student Projects

Sachgebiet: Computer Vision

You will be working camera, lidar and radar sensor data!
Topic 3D Perception and Multi-modal Sensor Fusion
Type Forschungspraxis(FP), Interdisziplinäres Projekt (IDP), Master's Thesis
Supervisor Philipp Wolters
E-Mail: philipp.wolters@tum.de
Area Machine Learning for Computer Vision
Description

We are currently looking for motivated Master's students who want to do their thesis or research practical in the fields of 3D object detection, tracking and/ or multi-modal sensor fusion (camera + radar).

  • Research and analyze the latest deep learning techniques and models for 3D computer vision and scene understanding in the context of autonomous driving.
  • Implement state-of-the-art algorithms and models in Python and PyTorch.
  • Develop novel approaches for multi-modal sensor fusion, combining camera and radar data for improved object detection and tracking in challenging environments.
  • Work with large-scale datasets for 3D object detection and tracking, including KITTI, Waymo, and nuScenes.
  • Transform research concepts into working prototypes.
  • Collaborate with our industry partner on real-world applications of your research.
Requirements
  • Pursuing a master’s degree in Computer Science, Engineering, Mathematics or a related field
  • Strong programming skills in Python
  • Prior experience with Deep Learning (preferably Object Detection/Tracking)
  • Familiarity with PyTorch or other deep learning libraries and frameworks
  • Knowledge of 3D computer vision, sensor fusion, and perception concepts is a plus
  • Strong problem-solving and analytical skills, with a passion for innovation and technology
Application Interested in working at the intersection of machine learning, computer vision and autonomous driving? Reach out via philipp.wolters@tum.de with your latest CV and transcript of records.
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