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Research Assistant (SSI)

Closes:

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Job Title: Research Assistant (SSI)

University-Level Unit: Smart Systems Institute

Faculty/Department-Level Unit: Smart Systems Institute

Employee Category: Research Staff

Location: Kent Ridge Campus

Posting Start Date: 04/08/2026

Job Description

The Research Assistant will develop the core components of the Data Engine Minimum Viable Product (DEM), an end-to-end system for collecting, curating and leveraging large-scale robot manipulation data for training generalist robot policies.

Specific duties include:

  • Develop automated data quality assessment methods, including uncertainty quantification and out-of-distribution detection, to identify and filter low-quality or unsafe demonstrations.
  • Build and maintain teleoperation and data-collection rigs for real robot platforms, including motion retargeting, inverse kinematics and bimanual/whole-body control.
  • Train, fine-tune and benchmark vision-language-action (VLA) and imitation learning policies on curated datasets; run systematic studies on data scale, mixture and augmentation. Optimise policy inference for real-time deployment on physical robots.
  • Maintain a well-documented, reproducible research codebase and support dataset and software releases.
  • Contribute to publications, technical reports and progress reports to the funding partner; present findings at project and group meetings.
  • Mentor student assistants and interns, and collaborate with project partners and other lab members.

Qualifications and Requirements

  • Master's degree in Electrical/Electronic Engineering, Computer Science, Mechanical Engineering, Robotics or a related discipline.
  • Strong programming ability in Python and C++, with hands-on experience in ROS/ROS2.
  • Practical experience with real robot manipulators, including teleoperation, retargeting, inverse kinematics or optimal/adaptive control.
  • Experience training deep learning models in PyTorch, with working knowledge of imitation learning / behaviour cloning and vision-language-action or large multimodal models.
  • Experience building large-scale data pipelines — dataset curation, standard robot data formats, versioning and quality control — is an advantage.
  • Track record of peer-reviewed publications at robotics or machine learning venues (e.g. CoRL, ICRA, IROS, RSS, NeurIPS) preferred.
  • Good written and spoken English; able to work independently as well as in a collaborative, multi-disciplinary team.

Req ID: 33960

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Job details

Title
Research Assistant (SSI)
Employer
National University of Singapore
Location
Kent Ridge Campus
Published
Aug 11, 2026
Closes:
Oct 10, 2026
Job type
Full time, Staff / Administration
Field
Laboratory and Research

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Frequently Asked Questions

🎓What are the minimum qualifications for this Research Assistant role?

You must hold a Master’s degree in Electrical/Electronic Engineering, Computer Science, Mechanical Engineering, Robotics, or a related field. Strong programming skills in Python and C++, hands‑on experience with ROS/ROS2, and practical work with real robot manipulators are essential. Familiarity with PyTorch and deep learning is required. Preferred qualifications include a track record of peer‑reviewed publications at top venues (CoRL, ICRA, IROS, RSS, NeurIPS). Explore our research assistant jobs for more context on typical requirements.

💻What are the main technical skills needed?

You need proficiency in Python and C++, experience with ROS/ROS2, and solid knowledge of PyTorch for training deep learning models. Must be comfortable with imitation learning/behaviour cloning and vision-language-action (VLA) policies. Practical skills in inverse kinematics, teleoperation, and bimanual control are crucial. Familiarity with building large-scale data pipelines and working with standard robot data formats is a strong advantage.

🤖What will my day-to-day work involve?

You will develop the Data Engine Minimum Viable Product (DEM), an end‑to‑end system for collecting and curating robot manipulation data. Tasks include building and maintaining teleoperation rigs, performing dataset quality assessment (e.g., uncertainty quantification), training and benchmarking imitation learning policies, and running systematic studies on data scale and augmentation. You will also contribute to publications, progress reports, and mentor student assistants.

🏢Is this a remote or on-site position?

The role is based at the Kent Ridge Campus of the National University of Singapore (NUS), within the Smart Systems Institute (SSI). Working with physical robot platforms requires on‑site presence; remote work is not mentioned.

📝How do I apply for this job?

Submit your application through the online application portal. You will need an updated CV, cover letter, and optionally a list of publications. For tips on crafting your academic CV, see our guide on how to write a winning academic CV. The application deadline is 10 October 2026.

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