Research Assistant (Humanoid Robotics), School of Computing

NATIONAL UNIVERSITY OF SINGAPORE; Singapore; On-site; SGD 42,000 - 66,000; Full time

Job summary

The National University of Singapore invites applications for a Research Assistant to work on cutting-edge humanoid robotics research, spanning graphics, physics-based simulation, and embodied AI. You will contribute to simulation, motion generation, and learning-based control, while supporting experiments and publications.

Collaborating with Assistant Professor Dr. Duan Jiafei, you will help develop tools, run experiments, and mentor students, advancing state-of-the-art in robotics research.

Qualifications

• Good understanding of computer graphics, such as physics-based simulation, character animation, motion capture, or rendering.
• Proficiency in Python and/or C++, with experience in relevant frameworks or tools (e.g., PyTorch, Isaac Gym/Lab, MuJoCo).
• Good analytical, problem-solving and programming skills.
• Ability to work independently on assigned tasks and collaboratively within a research team.
• Experience with humanoid robots, robotics simulation or legged locomotion would be an advantage.
• Familiarity with reinforcement learning or imitation learning for motion control would be an advantage.
• Prior research experience or contributions to research publications would be an advantage.

Responsibilities

• Assist in conducting research on humanoid robotics, including simulation, motion generation and control.
• Support the development, implementation and testing of algorithms using computer graphics techniques, such as physics-based simulation, character animation and 3D modelling, for humanoid applications.
• Conduct experiments, collect and analyse data, and evaluate research outcomes.
• Assist in developing and maintaining simulation environments, research software and experimental tools.
• Support the preparation of research publications, technical reports and presentations.
• Provide technical support to graduate and undergraduate students involved in research projects.
• Assist with project documentation, progress reports and other research-related activities.

Skills

Python

C++

PyTorch

MuJoCo

Robotics

Tools

PyTorch

Isaac Gym

MuJoCo

Job description

Job Description

We are seeking a highly motivated Research Assistant to conduct cutting-edge research on humanoid robotics. The successful candidate will work on topics at the intersection of robotics, computer graphics, and embodied AI, including physics-based simulation, character animation, motion synthesis, and learning-based control for humanoid systems.

Key Responsibilities:

• Assist in conducting research on humanoid robotics, including simulation, motion generation and control.

• Support the development, implementation and testing of algorithms using computer graphics techniques, such as physics-based simulation, character animation and 3D modelling, for humanoid applications.

• Conduct experiments, collect and analyse data, and evaluate research outcomes.

• Assist in developing and maintaining simulation environments, research software and experimental tools.

• Support the preparation of research publications, technical reports and presentations.

• Provide technical support to graduate and undergraduate students involved in research projects.

• Assist with project documentation, progress reports and other research-related activities.

The successful candidatewill be responsible for working closely with Assistant Professor Dr. Duan Jiafei (https://duanjiafei.com/)

Qualifications

• Good understanding of computer graphics, such as physics-based simulation, character animation, motion capture, or rendering.

• Proficiency in Python and/or C++, with experience in relevant frameworks or tools (e.g., PyTorch, Isaac Gym/Lab, MuJoCo).

• Good analytical, problem-solving and programming skills.

• Ability to work independently on assigned tasks and collaboratively within a research team.

• Experience with humanoid robots, robotics simulation or legged locomotion would be an advantage.

• Familiarity with reinforcement learning or imitation learning for motion control would be an advantage.

• Prior research experience or contributions to research publications would be an advantage.