We predominantly teach in the focus areas of "Autonomous Systems" and "Data Science" in the Bachelor's and Master's degree programs of the Faculty of Computer Science and Engineering:
Bachelor
Statistics
Signals and Systems
Digital Signal Processing
Sensors and Actuators
Autonomous Systems Design
Embedded Systems Design
Machine Learning
Machine Vision
Master
Theoretical Computer Science
Artificial Intelligence
Advanced Data Mining
Intelligent Time Series Analytics
Automotive System Design
Computer Vision & Deep Learning
Data Fusion
Motion Planning
Are you fascinated by the potential of intelligent systems and eager to contribute to cutting-edge research projects? At the Institute for Intelligent Systems (IIS), we offer research-oriented Bachelor’s and Master’s theses, as well as student research and project opportunities, all closely aligned with our current scientific focus areas.
Some of our open topics are published on the job board of the IT faculty (internal link). However, as our field is evolving rapidly, the majority of theses and student projects are assigned individually and are closely tied to our ongoing research projects and publications.
If you are interested in working with us, please follow these steps:
Familiarize yourself with our projects and read the recent publications that you find most interesting. IEEE Xplore access is provided by Esslingen University.
Develop a concrete research question or thesis / project idea that aligns with our current research.
Contact our PhD students (or, if appropriate, professors) via email and describe your proposed research question or thesis / project idea, including how it relates to our ongoing work and publications. Our PhD students also have their own topic suggestions, which can be discussed and refined together.
We expect from you:
A strong interest in research-driven, scientifically demanding questions in the field of intelligent systems.
Solid knowledge of mathematics, excellent programming skills (particularly in Python), confidence using Linux / Shell / git, and ideally experience with deep learning frameworks such as PyTorch, TensorFlow, or JAX.
Foundational knowledge in areas such as signal processing, autonomous systems, or machine learning, acquired through relevant Bachelor’s or Master’s courses (e.g., Machine Learning, Machine Vision, Artificial Intelligence) or through independent practical experience.
The willingness to regularly present and discuss your progress in our internal IIS seminar sessions within the research group.
