PhD Student

• Researching and developing methods for coordinating autonomous robots in connected production environments, focusing on decentralized decision-making and multi-agent systems
• Designing and implementing real-time capable AI algorithms for planning, navigation, and dynamic task allocation
• Applying reinforcement learning, edge AI, and sensor fusion to create adaptive systems for changing environments
• Using digital twins and Sim2Real transfer to efficiently translate simulation results to real-world robotic platforms
• Developing and integrating multimodal control concepts (e.g., Vision-Language-Action Models) and designing intuitive human-robot interactions in collaborative scenarios

• Good to very good university degree qualifying for doctoral studies in computer science, robotics, electrical engineering, mechanical engineering, or related fields
• Solid knowledge in at least one of the following areas: machine learning / deep learning, robotics / ROS / control engineering, computer vision
• Programming experience (e.g., Python, C++, ROS)
• Interest in interdisciplinary research and complex systems
• Independent, structured working style combined with strong team skills
• Ideally, initial experience with real robotic systems or simulations (e.g., Gazebo, Isaac Sim, Omniverse)

Initial experience with real robotic systems or simulations (e.g., Gazebo, Isaac Sim, Omniverse)

• Attractive salary & 30 vacation days (+ 24.12. and 31.12. off)
• 35-hour week, flexible working hours, remote work
• Special conditions for the purchase and leasing of vehicles
• Free seminars on scientific work and interdisciplinary qualifications
• Participation in the doctoral network for scientific exchange with science representatives and other doctoral candidates within the Volkswagen Group