Internship Lifelong Learning for Humanoid Robots

The future of robotics lies in continuous learning—a vision that empowers robots to evolve autonomously and throughout their entire operational lifespan. Are you ready to stand at the forefront of this revolution and create humanoid systems that do not merely follow instructions, but actively learn? With us, you will shape the next generation of intelligent robots—systems that constantly refine their capabilities through visual feedback and verbal commands.

• During your internship, you implement and evaluate a pioneering system for continuous learning deployed on a humanoid robot.
• You enable the robot to autonomously acquire and refine new manipulation skills, based on real-time visual feedback and verbal commands.
• Lastly, you precisely fine-tune pre-trained VLA models using Parameter-Efficient Fine-Tuning (PEFT) and continuous learning techniques, such as Experience Replay, to realize lifelong skill acquisition.

• Education: Master studies in Computer Science, Robotics, Artificial Intelligence, or comparable with excellent academic records
• Experience and Knowledge: solid practical experience in Machine Learning, particularly with deep learning frameworks such as PyTorch; strong programming skills in Python; proficiency in working within a Linux environment; fundamental understanding of robotics (e.g., kinematics), computer vision, and NLP; ideally, prior experience working with robotic hardware or within a robotics simulation environment; knowledge of a robotics framework such as ROS (Robot Operating System) is desirable
• Personality and Working Practice: you work independently and with high motivation, navigating complex technical landscapes with confidence and proactively tackling new challenges
• Work Routine: with us, you benefit from a hybrid model that enables you to work both in the office and remotely
• Languages: very good in English

Start: according to prior agreement
Duration: 6 months

Requirement for this internship is the enrollment at university. Please attach your CV, transcript of records, enrollment certificate, examination regulations and if indicated a valid work and residence permit.

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.

Need further information about the job?
Matthias Neuwirth-Trapp (Functional Department)
+49 152 04994 800

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