Research Associates and Doctoral Candidates

We currently do not have any vacancies for funded positions. If you want to apply for self- or externally-funded positions, please reach out to us via

Student and Research Assistants

If you are interested in a student research assistant position in one of our research projects, please contact the staff involved directly.

The Chair of Remote Sensing Technology is a joint appointment of TUM and the German Aerospace Center (DLR). We explore and develop machine learning and computer vision approaches to solve problems in satellite-based remote sensing and Earth observation. A particular focus is on the processing of geospatial data while taking into account and exploiting their special properties.

For the upcoming summer semester 2024, we are looking for several student assistants to support us in the preparation and execution of our courses and tutorials. These are mainly aimed at students of geodesy and geoinformatics, as well as aerospace engineering, and include courses on the topics of

  • Computer Vision

  • Machine Learning

  • Recent and trending research approaches in machine learning

  • Practical student projects

  • Signal processing and systems theory

  • Estimation theory

Depending on your personal interests and skills, you can contribute to the preparation of teaching and learning materials, the maintenance of the learning platforms used (Moodle, Perusall, gitlab), the implementation of tutorials and exercises or the supervision of student work. Contracts can be awarded flexibly in the range of 8 to 20 hours per week. The new student assistants are expected to work together as a team and support each other.


  • Completed bachelor's degree in a technical field of study (computer science, electrical engineering, mathematics, ...)

  • successful attendance of courses on the above-mentioned topics

  • practical experience in programming in Python as JupyterLab notebooks and creating documents in LaTeX

  • interest in teaching methodological and technical content to students in our master's programs.

We would like to explicitly address students from all schools and study programs, no special previous experience in processing geospatial data is required. If you are interested or have any questions, please contact Prof. Dr. Marco Körner ( Please attach a short CV and an overview of the courses you have attended to your application.