Research Fellow (Robotic Inspection)

National University of Singapore; Singapore; On-site; SGD 60,000 - 100,000; Full time

Job summary

The National University of Singapore invites applications for a Research Fellow to work on robotic scanning, 3D perception, inspection and last-mile navigation in construction or infrastructure environments. The successful candidate will hold a PhD and have expertise in LiDAR/SLAM, ROS/ROS2, Linux, and strong programming skills.

Experience in 3D mapping, traversability analysis and GPS-denied navigation is desirable.

Qualifications

• PhD in a relevant field with a strong research background.
• Proficiency with LiDAR, SLAM, and 3D mapping.
• Experience with ROS/ROS2 and Linux.
• Background in GPS-denied navigation and robot planning.

Responsibilities

• Collaborate with the research team on robotic perception and navigation.
• Contribute to planning and executing research projects.
• Mentor postgraduate students and research staff.
• Publish findings in peer-reviewed venues.

Skills

SLAM

LiDAR

3D perception

Programming

ROS/ROS2

Linux

Education

PhD degree

Tools

SLAM frameworks

Job description

Company description

The National University of Singapore is the national research university of Singapore. Founded in 1905 as the Straits Settlements and the Federated Malay States Government Medical School, NUS is the oldest higher education institution in Singapore

Job Description

We are seeking a Research Fellow to work on robotic scanning, 3D perception, inspection and last-mile navigation in construction or infrastructure environments. Interested applicants are invited to submit their CV and selected publications, if available, to Assistant Professor Vincent Gan at ••••@nus.edu.sg before 30 Nov 2026. Shortlisted candidates will be contacted for further discussion.

Job Requirements

The candidate should have a PhD degree* with background in the following areas:

• Proficiency in laser scanning, LiDAR, and Simultaneous Localization and Mapping (SLAM), including open-source frameworks and algorithms for 3D scene reconstruction.
• Experience in 3D perception, mapping, localization, ground robot navigation, and collision avoidance.
• Familiarity with ROS/ROS2 and Linux platforms, as well as strong programming skills, is expected.
• The candidate will also contribute to research in semantic 3D mapping, traversability analysis and robot trajectory optimisation, especially for GPS-denied, cluttered environments. LiDAR-based object detection algorithms and integrating real-time inference for deployment on robotic platforms.
• The candidate will also implement the integration of perception and robot navigation components for last-mile navigation experiments.
• Candidates should demonstrate knowledge and expertise in the aforementioned areas, with a proven track record of peer-reviewed publications.
• The appointed candidate will support the planning and execution of research projects together with postdoctoral researchers, PhD students, and research assistants within the research group and the Centre for Digital Building Technology.

(* Candidates who are in the final stages of PhD studies (i.e. submitted thesis; pending oral defence) may also be considered)