Research Associate (Robotics)

About the role

The Research Associate will support research on robot navigation, focusing on integrating visual perception, localization, planning and navigation. The role involves designing navigation algorithms for inspection robots in complex, dynamic environments, including global and local motion planning, obstacle avoidance and trajectory generation. You will investigate learning-based approaches such as diffusion models and reinforcement learning for navigation decision-making and adaptive robot behaviour. The position also includes building and evaluating algorithms in simulation and on real-world humanoid robotic platforms, contributing to publications, and assisting in mentoring students.

Requirements

• Master's degree in Robotics, Mechanical Engineering, Electrical Engineering, Computer Science, or related fields
• Strong background in robot motion planning and control, autonomous decision-making, or robot localization and navigation
• Experience in path planning, motion planning, trajectory optimization or model predictive control; reinforcement learning, imitation learning or learning-based control; diffusion policies or generative decision-making; or robotics physics simulators (e.g., Isaac Gym, MuJoCo, Gazebo)
• Proficiency in Python and/or C++
• Experience with PyTorch or similar deep learning frameworks
• Strong problem-solving ability and hands-on implementation skills