Working Student, Control and Learning for Humanoid Robots (m/f/d)

<p><strong>About the role</strong></p> <p>Agile Robots SE is a high-tech startup based in Munich. Our mission is to bridge the gap between AI and robotics by developing robotic systems that offer state-of-the-art full-body force sensitivity and world-leading vision intelligence. This unique combination of technologies enables us to provide intelligent, easy-to-use and affordable robotic solutions with safe human-robot interaction.</p> <p>We are a dynamic and innovative software development company dedicated to pushing the boundaries of technology. We specialize in creating cutting-edge solutions that transform industries and redefine user experiences.</p> <p>We are looking for motivated students interested in control and learning for humanoid robots. Depending on your background, interests, and the current project needs, you will contribute to research and development topics at the intersection of robot learning, control, simulation, and real-world robotic systems.</p> <p>The work may involve developing and evaluating learning-based control policies, improving simulation and training pipelines, analyzing robot behavior, or supporting the transfer of algorithms from simulation to real robotic platforms.</p> <p>This role is well suited for students who are curious, technically strong, and interested in working on open-ended robotics problems where not all requirements are known in advance.</p> <p>&nbsp;</p> <p><strong>Your Responsibilities</strong></p> <ul> <li>Developing, testing, and improving control and learning algorithms for humanoid robots</li> <li>Working with simulation environments for training, evaluation, and benchmarking</li> <li>Supporting reinforcement learning, imitation learning, or model-based learning pipelines</li> <li>Implementing and evaluating locomotion, manipulation, balancing, or whole-body control behaviors</li> <li>Analyzing robot behavior, failure cases, and learning performance</li> <li>Supporting sim-to-real transfer and experiments on robotic hardware</li> <li>Integrating learned policies with perception, planning, control, and actuation components</li> <li>Reviewing and reproducing relevant research from robotics, control, and machine learning</li> <li>Documenting results clearly and presenting technical findings to the team</li> </ul> <p>&nbsp;</p> <p><strong>Your Profile</strong></p> <ul> <li>Currently enrolled in a Master’s degree in robotics, computer science, electrical engineering, mechanical engineering, artificial intelligence, or a related field</li> <li>Strong interest in humanoid robotics, robot learning, control, or embodied AI</li> <li>Good programming skills in Python and/or C++</li&gt