Research Assistant

SUTD; Singapore; On-site; SGD 60,000 - 100,000; Full time

Job summary

SUTD invites engineers and graduates to join a hands-on robotics research team focused on learning-based intelligence for real robots connected over wireless networks. You will set up robot platforms in ROS 2, collect demonstration data, and train vision-language-action models for deployment on physical robots.

Collaborating with wireless engineers and industry partners, you will study how robot intelligence performs in real-world settings, contribute to publications and demonstrations, and

Qualifications

• Bachelor’s or Master’s degree in Robotics, Computer Science, Electrical Engineering, Mechatronics, or related field.
• Hands-on experience building or programming real robots, demonstrated via capstone projects, internships, or open-source work.
• Proficiency in Python; experience with PyTorch or another deep learning framework.
• Experience with ROS/ROS 2 and Linux.
• Familiarity with robot learning such as imitation learning, VLA models, or world models.
• Hands-on experience training or deploying learned policies on robots, including teleoperation data collection.

Responsibilities

• Conduct hands-on research to develop and deploy learning-based intelligence on real robots.
• Set up and integrate robot platforms in ROS 2, and collect demonstration data.
• Train and fine-tune robot learning models and deploy them on physical robots.
• Collaborate with wireless engineers and industry partners to test in real-world settings.
• Contribute to research publications and demonstrations.

Skills

Python

PyTorch

Imitation learning

VLA models

World models

Teleoperation data collection

Teamwork

Education

Bachelor’s or Master’s in Robotics/CS/EE/Mechatronics

Tools

ROS/ROS 2

Linux

Isaac Sim

MuJoCo

Gazebo

NVIDIA Jetson

C++

Job description

About the Job:

You will conduct hands-on research to develop and deploy learning-based intelligence on real robots connected over wireless networks. You will set up and integrate robot platforms in ROS 2, collect demonstration data, train and fine-tune robot learning models such as vision-language-action (VLA) models, and deploy them on physical robots. Working with wireless engineers and industry partners, you will study how robot intelligence performs in connected, real-world settings. You will contribute to research publications and demonstrations. Fresh graduates and early-career engineers with strong hands-on project experience are encouraged to apply.

Who We’re Looking For:

• Bachelor’s or Master’s degree in Robotics, Computer Science, Electrical Engineering, Mechatronics, or related field.
• Hands‑on experience building or programming real robots, e.g., through capstone projects, robotics competitions, internships, or open‑source projects, demonstrated through code repositories or demo videos.
• Proficiency in Python; experience with PyTorch or another deep learning framework.
• Experience with ROS/ROS 2 and Linux.
• Familiarity with, or strong interest in, robot learning such as imitation learning, VLA models, or world models.
• Hands‑on experience training or deploying learned policies on robots (e.g., with LeRobot), including teleoperation data collection, is highly valued.
• Experience with robot simulators (e.g., Isaac Sim, MuJoCo, Gazebo), embedded GPUs (e.g., NVIDIA Jetson), or C++ is a plus.
• Experience with robot arms, mobile robots, or humanoid robots, and interest in wireless or networked robotics, is a plus.
• Eagerness to learn, problem‑solving skills, and the ability to work in a team.