Working Student Control and Learning for Humanoid Robots

Skills

About the Role

You will develop, test, and improve control and learning algorithms for humanoid robots. You will use simulation environments, support learning pipelines, evaluate robot behaviors, analyze failures and performance, conduct sim-to-real hardware experiments, integrate learned policies, review research, and document technical findings.

Requirements

• Current enrollment in a master's degree in robotics, computer science, electrical engineering, mechanical engineering, artificial intelligence, or a related field
• Programming skills in Python and/or C++
• Basic understanding of robot kinematics, dynamics, control, or motion planning
• Familiarity with machine learning, reinforcement learning, imitation learning, or optimization
• Communication and interdisciplinary collaboration skills

Responsibilities

• Develop, test, and improve control and learning algorithms for humanoid robots
• Use simulation environments for training, evaluation, and benchmarking
• Support reinforcement learning, imitation learning, and model-based learning pipelines
• Implement and evaluate locomotion, manipulation, balancing, and whole-body control behaviors
• Analyze robot behavior, failure cases, and learning performance
• Support sim-to-real transfer and robotic-hardware experiments
• Integrate learned policies with perception, planning, control, and actuation components
• Review and reproduce robotics, control, and machine-learning research
• Document results and present technical findings

Benefits

• Corporate Benefits Program covering health, mobility, and learning with €100 net per month
• Modern office facilities with a rooftop terrace
• Free drinks and fruit
• Regular company events