Research Assistant (SLAM and Perception for Robotic Assembly)

National University of Singapore; Singapore; On-site; SGD 33,000 - 61,000; Full time

Job summary

National University of Singapore’s Civil and Environmental Engineering department seeks a Research Assistant for the Constructive Machines Lab. You will develop SLAM and state estimation for dynamic environments with multi-robot coordination to support planning and perception.

Initial work is in simulation, transitioning to hardware as available. The role requires strong C++/Python skills, ROS/ROS2 experience, and a background in 3D reconstruction and perception.

Qualifications

• Bachelor's degree in CS, EE, ME, Robotics or related field.
• Master's degree preferred.
• Strong SLAM and state estimation fundamentals incl. LiDAR/IMU and VO.
• Proficient in C++ and/or Python; ROS/ROS2 experience.
• Experience with 3D reconstruction, TSDF/occupancy mapping.
• Experience with learning-based perception (PyTorch).
• Familiarity with robotics simulators (Isaac Sim, MuJoCo, Gazebo).
• Experience deploying perception on real robots with LiDAR/cameras.
• Able to work independently and in multidisciplinary team.
• Strong written and spoken communication skills.
• Open to fixed-term contract.

Responsibilities

• Develop and evaluate SLAM and state estimation for changing environments.
• Perceive and track structure against design with pose estimation.
• Develop multi-robot state estimation and map merging.
• Implement active perception with task-and-motion planning.
• Benchmark methods in simulation and deploy on lab platforms.

Skills

SLAM

State estimation

LiDAR/IMU odometry

Factor-graph

Loop closure

C++/Python

ROS/ROS2

3D reconstruction

Point cloud

Mesh reconstruction

PyTorch

Pose estimation

Robotics simulation

Real robot deployment

Teamwork

Communication

Education

Bachelor's degree

Master's degree preferred

Tools

ROS/ROS2

MuJoCo

Gazebo

Isaac Sim

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

The Department of Civil and Environmental Engineering at the National University of Singapore (NUS) invites applications for one (1) Research Assistant position in the Constructive Machines Lab. The lab builds robotic systems that autonomously build structures and studies the two-way relationship between how a structure is designed and how it is built. Its current focus is a team of mobile manipulators that transport and assemble scaffolding systems, temporarily support unstable partial assemblies, and progressively turn the structure-in-progress into navigable space for themselves.

This position addresses the perception problem that follows from that premise: the robots operate in an environment they are themselves rebuilding, so the map cannot be assumed static. The successful candidate will develop simultaneous localisation and mapping for a world under construction, maintaining a consistent shared estimate of the structure's true as-built state across a team of robots, and closing the loop with the planning system so that perception is driven by what the plan actually needs to know. Work will begin in simulation and move onto the physical platforms as the lab's hardware comes online.

Research Assistant is expected to:

• Develop and evaluate SLAM and state estimation methods for environments that change as the robots build, where newly placed structural elements must be incorporated into the map.
• Perceive and track the partially built structure against the design model, including element-level pose estimation, deviation detection, and reporting the as-built state back to the planner.
• Develop multi-robot state estimation, including map merging, co-localisation, and consistent reference frames across heterogeneous platforms.
• Implement task-and-motion-planning-informed active perception, in which viewpoint and sensing decisions are selected according to the information the planner requires.
• Benchmark methods in simulation and deploy them on the lab's mobile manipulation platforms in collaboration with the hardware team.

Job Requirements

• At least a Bachelor's degree in Computer Science, Electrical Engineering, Mechanical Engineering, Robotics, or a related field.
• A Master's degree will be preferred.
• Solid understanding of SLAM and state estimation fundamentals, including LiDAR-inertial and visual-inertial odometry, factor-graph optimisation, and loop closure.
• Strong programming skills in C++ and/or Python, with working experience in ROS or ROS 2.
• Experience with 3D reconstruction and scene representation, such as occupancy or TSDF mapping, point cloud registration, and mesh reconstruction.
• Experience with learning-based perception, including object and structural element detection and 6-DoF pose estimation, with PyTorch or a comparable framework.
• Familiarity with robotics simulation platforms such as Isaac Sim/Lab, MuJoCo, or Gazebo is preferred.
• Experience deploying perception systems on real robots with LiDAR and camera sensing is highly preferred.
• Ability to work both independently and collaboratively within a multidisciplinary research team.
• Strong written and spoken communication skills.
• Open to fixed-term contract.