Open Positions: Postdoctoral Researchers & Research Assistants

The CLeAR Lab at the National University of Singapore is recruiting multiple Postdoctoral Researchers and Research Assistants (RAs) to join our group starting in 2026.

Representative work and ongoing projects can be found at:
https://clear-nus.github.io

Postdoctoral Positions – Research Areas

We are seeking postdoctoral researchers working in robot learning and robot foundation models, including (but not limited to):

• Skill learning, hierarchy, and compositional behaviors
• Instruction following, reward learning, and preference inference
• Fast adaptation from human instructions
• Learning in embodied, interactive environments

In addition, we are actively seeking postdoctoral researchers interested in:

• Trustworthy robot foundation models and systems
• Reliability, robustness, and deployment considerations for learning-based robots
• Real-world robotic systems, including hands-on experience with physical robots

Important:
Candidates in this second category must have experience working with real robotic platforms. If your work lives entirely in simulation, this is likely not the right fit.

Research Assistants (RAs) – Research Areas

We are also hiring Research Assistants interested in:

• Robot learning and robot foundation models
• Implementing, testing, and deploying learning systems on real robots
• Supporting experimental, system-building, and data collection efforts

RAs are expected to be technically strong, proactive, and comfortable working closely with robotic hardware and software stacks.

Who We Are Looking For

Across all positions, we are looking for motivated researchers capable of independent, high-quality work. Ideal candidates:

• Have strong fundamentals in robotics, machine learning, or AI
• Can drive projects from idea to implementation
• Care about grounding learning in real, embodied systems
• Are curious, rigorous, and not afraid of debugging robots
• Communicate well and are happy to work in a team

Publications, systems experience, and research maturity matter more than buzzwords.

Application

Please email your application materials to harold@nus.edu.sg.

Email subject line:
[Postdoc/RA Application – Your Name – Your Current Affiliation]

Please include:

• CV
• Brief research statement or cover letter
• Representative publications or projects (if available)

Only shortlisted candidates will be contacted for an interview.

If you are interested in building robot learning systems that adapt quickly, follow human intent, and survive contact with the real world, we encourage you to apply.