Fraunhofer-Gesellschaft is looking for a Master's student to undertake a thesis in Multi-Agent System Reinforcement Learning. You will contribute to research under supervision, building on previous work for real-world use cases in Aerial Ad-hoc Networks. The project aims to improve the solution using modern MARL methods.
What You'll Do
- Contribute to research in Multi-Agent Reinforcement Learning for Aerial Ad-hoc Networks.
- Work on improving an existing solution using modern MARL methods with a focus on scalability and reliability.
What We're Looking For
- Experience with the Python ML stack (e.g., TensorFlow, Stable-Baselines3).
- Solid knowledge of Reinforcement Learning.
- Familiarity with Multi-Agent Systems and/or Game Theory.
- Familiarity with Linux operating systems and Git.
- Enrollment at a German university, preferably in Munich or the surrounding area.
Nice to Have
- Particularly suitable for students of M.Sc. Computer Science, M.Sc. Robotics, Cognition, Intelligence, M.Sc. Data Engineering, etc.
Technical Stack
- Python, TensorFlow, Stable-Baselines3
- Linux, Git
Team & Environment
You will collaborate in a dynamic team with innovative task areas.
Benefits & Compensation
- Nice supervisors, pleasant working atmosphere, hybrid working model.
- Flexible working style, including a workspace in the new institute building in Garching.
- Collaboration in a dynamic team with innovative task areas.
- Practice-oriented study approach.
Work Mode
This is a hybrid position based in Garching.
We value and promote the diversity of our employees' skills and therefore welcome all applications - regardless of age, gender, nationality, ethnic and social origin, religion, worldview, disability as well as sexual orientation and identity. Severely disabled persons will be given preferential consideration if they are equally qualified.
