Robotics / Physical AI Intern

Robotics / Physical AI Intern

We are looking for an MSc or PhD student to join our Physical AI team and support the calibration, control, and evaluation of robotic systems. The ideal candidate is rigorous, hands-on, and comfortable moving between simulation, robotics theory, ROS 2 nodes, calibration scripts, robot logs, and real-world experiments.

Responsibilities

Develop and evaluate calibration procedures for robotic systems and sensors.

Implement and test low-level control methods, including position, velocity, impedance, and force-related control where relevant.

Work with ROS 2-based robotic software stacks for system integration, data collection, and experiment automation.

Design and conduct repeatable experimental protocols, including data collection, validation, and analysis of robot performance (accuracy, stability, robustness, task success).

Support debugging of hardware-software interactions in real robotic setups.

Contribute to research prototypes, internal technical reports, and publications.

Requirements

Current MSc or PhD student in robotics, control, mechanical engineering, electrical engineering, computer science, or a related field.

Strong and independent researcher and learner

Understanding of classical robotics, including kinematics, dynamics, control.

Experience with ROS 2, or strong ROS experience with willingness to work in ROS 2.

Good programming skills in Python and/or C++.

Ability to design experiments, document results, reason quantitatively about results.

Preferred

Experience with simulators such as Isaac

Experience with robot calibration, hand-eye calibration, camera calibration, motion capture, force/torque sensing, or repeatability analysis.

Prior research in physical AI.