Master Thesis Reinforcement Learning for Behavior Planning in Automated Driving

Job Description

Work on cutting‑edge AI topics during your thesis and gain hands‑on experience in an innovative environment. Ready to make an impact? Apply now and shape the future of automated driving!

Responsibilities

• During your thesis, you will review scientific literature on state‑of‑the‑art approaches to behavior planning in automated driving, with a particular focus on Reinforcement Learning (RL).
• You will become familiar with available open‑source datasets as well as training and simulation frameworks used in autonomous driving.
• Building on this foundation, you will design novel training methodologies and apply them to train high‑performance AI planners for autonomous driving applications.
• By integrating Imitation Learning (IL) and Reinforcement Learning, you will leverage the advantages of both approaches within a combined framework.
• Throughout your work, you will ensure well‑structured technical documentation and maintain clean code.

Qualifications

• Education: Master studies in the field of Computer Science, Artificial Intelligence, Robotics, Mechatronics or comparable with very good grades
• Experience and Knowledge:
  • familiarity with behavior planning for automated driving, and in particular, with AI‑based planners
  • strong theoretical background in Imitation Learning (IL) and Reinforcement Learning (RL)
  • excellent programming skills in Python
  • knowledge of collaborative coding and software development platforms, such as GitHub
  • C++ skills considered a plus
• Personality and Working Practice: you are highly motivated, open to collaboration and teamwork, and equipped with excellent communication skills
• Work Routine: your on‑site presence is required
• Languages: fluent in English

Requirement for this thesis is the enrollment at university.

Start: according to prior agreement
Duration: 6 months

EEO Statement

Diversity and inclusion are not just trends for us but are firmly anchored in our corporate culture. Therefore, we welcome all applications, regardless of gender, age, disability, religion, ethnic origin or sexual identity.