Research Engineer (Task and Motion Planning for Robotic Assembly)

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

Job summary

The Department of Civil and Environmental Engineering at the National University of Singapore (NUS) invites applications for one Research Engineer position in the Constructive Machines Lab. The lab builds robotic systems that autonomously build structures and studies how design and construction interact.

The role focuses on planning, sequencing, and multi-robot coordination for scaffold construction and automated assembly.

Qualifications

• Bachelor's degree in computer science, robotics, mechanical, electrical engineering or related field.
• Master's degree preferred.
• Strong grounding in robot motion planning and trajectory optimisation.
• Familiarity with symbolic planning, constraint programming or MIQP.
• Proficient in Python and/or C++ with clean, reproducible code.
• Experience with physics/robotics simulation platforms.
• Learning-based planning is a plus.
• Experience in research settings is highly valued.
• Able to work independently and in a multidisciplinary team.
• Excellent written and spoken communication.
• Open to fixed-term contract.

Responsibilities

• Develop and evaluate task and motion planning methods for assembly in progressively expanding configuration spaces.
• Formulate and solve assembly sequencing under structural constraints including temporary supports.
• Develop multi-robot task allocation and scheduling to minimise construction time.
• Implement and benchmark planning pipelines in simulation to quantify throughput.

Skills

Robot motion planning

Python

C++

PyTorch

Reinforcement learning

Multi-robot coordination

Strong communication

Independent & collaborative work

Education

Bachelor's in CS/Robotics/ME/EE

Master's degree preferred

Tools

Isaac Sim/Lab

MuJoCo

PyBullet

Drake

Gazebo

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

Job Description

The Department of Civil and Environmental Engineering at the National University of Singapore (NUS) invites applications for one (1) Research Engineer 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. The lab investigates both conventional planning pipelines and recent learning-based approaches, and the candidate will have the opportunity to work across both.

The Research Engineer is expected to:

• Develop and evaluate task and motion planning methods for assembly in environments whose reachable configuration space expands as construction proceeds.
• Formulate and solve assembly sequencing problems under structural stability constraints, including when temporary supports are required and which robot provides them.
• Develop multi-robot task allocation and scheduling methods that minimise total construction time for a given number of robots.
• Implement and benchmark planning pipelines in physics simulation and quantify achievable construction throughput across scenarios.

Job Requirements

• At least a Bachelor's degree in computer science, Robotics, Mechanical Engineering, Electrical Engineering, or a related field.
• A Master's degree will be preferred.
• Solid grounding in robot motion planning, including sampling-based planners, collision checking, inverse kinematics, and trajectory optimisation.
• Familiarity with task planning or combinatorial optimisation, such as symbolic planning, constraint programming, mixed-integer programming, or scheduling.
• Strong programming skills in Python and/or C++, with clean, well-documented, and reproducible code.
• Experience with physics simulation and robotics simulation platforms such as Isaac Sim/Lab, MuJoCo, PyBullet, Drake, or Gazebo.
• Experience with learning-based planning or decision-making, for example reinforcement learning or learned search heuristics with PyTorch, is a plus.
• Prior research experience in task and motion planning, assembly planning, or multi-agent coordination is highly preferred, including experience gained during a Master's or PhD programme.
• Ability to work both independently and collaboratively within a multidisciplinary research team.
• Strong written and spoken communication skills.
• Open to fixed-term contract.