Centre for Advanced Robotics Technology Innovation (CARTIN) are looking for a Research Associate with experience in radar and IMU odometry to join a cutting-edge SLAM project for harsh environments. The Research Associate will develop a radar-inertial fusion module using 4D imaging radar and IMU for robust ego-motion estimation under low visibility, with strong skills in SLAM, signal processing, sensor fusion, and ROS2 implementation.

Key Responsibilities:

• Design and implement real-time radar-inertial odometry algorithms.
• Extract ego-motion estimation from 4D radar and fuse with IMU data.
• Evaluate performance in degraded visual conditions (e.g., fog, rain, smoke).
• Integrate odometry outputs with downstream SLAM and mapping modules.
• Work closely with hardware and system integration teams.
• Perform test and validation in fire fighting environments

Job Requirements:

• Master’s degree in Robotics, EE, CS or related fields.
• Strong background in 4D radar point cloud processing, sensor fusion, Kalman filtering.
• Experience with point cloud based odometry, e.g., LOAM/ Fast-LIO/ LIO-SAM etc.
• Proficient in C++/ Python and ROS1/2.
• Familiar with real-world SLAM datasets and evaluation metrics.

We regret to inform that only shortlisted candidates will be notified.
Hiring Institution: NTU

• Design and implement real-time radar-inertial odometry algorithms.
• Extract ego-motion estimation from 4D radar and fuse with IMU data.
• Evaluate performance in degraded visual conditions (e.g., fog, rain, smoke).
• Integrate odometry outputs with downstream SLAM and mapping modules.
• Work closely with hardware and system integration teams.
• Perform test and validation in fire fighting environment