Research Assistant

Chinese University of Hong Kong

Duties & Responsibilities

Develop and implement autonomous learning-based robotic systems for complex surgical procedures using simulations and physical hardware.
Build realistic surgical simulation platforms using Isaac-SIM with rigid and soft object manipulation capabilities.
Implement and evaluate state-of-the-art imitation learning and reinforcement learning models for surgical tasks.
Transfer trained policies from simulation to physical robotic setups to bridge the sim-to-real gap.
Assist in setting up, debugging, and running real-world experiments with robotic arms and surgical instruments.

Bachelor's or Master's degree in Computer Science, Robotics, Engineering, or related disciplines.
Familiarity with theoretical foundations of imitation learning and reinforcement learning.
Hands-on experience with at least one robotics simulator (NVIDIA Isaac-Sim, Mujoco, Gazebo, Pybullet, or CoppliaSIM).
Solid understanding and practical experience with deep learning frameworks such as PyTorch.
Strong problem-solving skills and project execution capability with self-motivation and teamwork ability.
Preferred: prior experience with NVIDIA Isaac Sim, ROS/ROS2, multi-robot control, rigid/soft body simulation, and physical robotic hardware.

Full-time contract for one year, renewable subject to good performance and mutual agreement.