Job Description

This position involves working on a project focused on efficient multimodal robot learning for manipulation, with emphasis on vision-language-action (VLA) systems. The candidate will help in bridging simulation and real robot systems to enable robust, safe manipulation in real environments.

The candidate will:

•             Contribute to building manipulation pipelines that combine perception, language, and control.

•             Implement and evaluate safety and uncertainty-aware modules to monitor and filter robot behaviors.

•             Perform data collection, calibration, and annotation on robotic manipulators and mobile manipulation platforms (such as Mobile ALOHA).

•             Develop and maintain simulation environments in Isaac Lab / Isaac Gym / PyBullet / Gazebo for training and testing.

•             Work with large manipulation datasets (e.g. LIBERO, RoboCasa, DROID) to guide model training, generalization, and benchmarking.

•             Collaborate with the PI and research team to design experiments, analyze results, document findings, and support dissemination (e.g. internal reports, code releases).

Qualifications

•             Strong programming skills in Python (experience in C++ is a plus).

•             Experience with ROS / ROS2, and robotics simulation tools (e.g. Isaac Lab / Isaac Gym / PyBullet / Gazebo).

•             Background in robot manipulation, motion control, and trajectory planning.

•             Familiarity with vision-language models / architectures (VLMs/VLAs) or multimodal learning in robotics.

•             Experience or strong interest in robot data collection, teleoperation, calibration, and evaluation.

•             Exposure to large-scale manipulation datasets such as LIBERO, RoboCasa, DROID, or similar.

•             Preferred: experience with Mobile ALOHA or mobile manipulation platforms.

•             Good analytical, troubleshooting, and experimental design skills.

•             Ability to work independently as well as collaboratively within a research team.

More Information

Location: Kent Ridge Campus

Organization: College of Design and Engineering

Department : Mechanical Engineering

Employee Referral Eligible: No

Job requisition ID : 30741