As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to develop industry-relevant applied research skillsets while working on translational robotics and AI projects.

The primary responsibility of this role is to support a joint SIT–DSO research project focused on evaluating and developing humanoid robot capabilities for door opening and doorway traversal in human-centric environments. The Research Engineer will contribute to humanoid robot system integration, teleoperation-based data collection, simulation-based synthetic data generation using NVIDIA Isaac Sim, and learning-based policy development for manipulation and locomotion tasks. The role will involve both experimental robotics work and AI model development for sim-to-real humanoid manipulation research.

Key Responsibilities

• Participate in and manage the research project together with the Principal Investigator (PI), Co-PI, and research team members to ensure project deliverables are achieved.
• Undertake the following responsibilities in the project:
  1. Humanoid Robot System Integration
     • Configure and integrate humanoid robot hardware and software systems for door opening and doorway traversal tasks.
     • Support calibration, perception, locomotion, manipulation, and control pipeline integration.
  2. Experimental Testbed Development
     • Design and set up representative door interaction experimental environments.
     • Conduct baseline testing and benchmarking for humanoid manipulation and traversal tasks.
  3. Teleoperation and Data Collection
     • Develop and operate teleoperation pipelines for humanoid robot data collection.
     • Collect, process, and manage robot demonstration datasets including perception, robot states, and control data.
  4. Simulation and Synthetic Data Generation
     • Develop simulation environments and synthetic data generation workflows using NVIDIA Isaac Sim and Omniverse technologies.
     • Implement domain randomization and scenario variation pipelines for robust sim-to-real learning.
  5. AI Model Development
     • Support development and evaluation of learning-based control policies using reinforcement learning, imitation learning, and visuomotor learning approaches.
     • Assist in model training, testing, benchmarking, and deployment on real robotic platforms.
  6. Research and Technical Reporting
     • Conduct literature reviews and experimental studies related to humanoid robotics and sim-to-real learning.
     • Prepare technical reports, publications, and presentation materials for project reviews and dissemination.
     • Carry out Risk Assessment and ensure compliance with Workplace Safety and Health regulations.
     • Coordinate procurement and liaison with vendors/suppliers.
     • Work independently and within a multidisciplinary team to ensure proper operation and maintenance of robotics equipment and experimental infrastructure.
     • Assist in co-supervision of Final Year Project (FYP) or capstone students together with the project PI.
• To communicate and liaise with internal and external stakeholders to ensure project deliverables are met. Any other ad-hoc duties assigned by Supervisors.

Key Requirements

• Bachelor’s, Master’s, or PhD degree in Robotics, Mechanical Engineering, Electrical Engineering, Computer Science, or related fields.
• Experience in robotics software development using ROS/ROS2.
• Experience with robotic simulation platforms such as NVIDIA Isaac Sim, Isaac Lab, Gazebo, or MuJoCo.
• Familiarity with humanoid robots, robotic manipulators, or locomotion systems.
• Knowledge of machine learning, reinforcement learning, imitation learning, or computer vision techniques for robotics applications.
• Strong analytical and problem-solving skills.
• Good written and verbal communication skills.
• Ability to work independently and collaboratively in multidisciplinary teams.
• The following will be advantageous:
  • • Experience with teleoperation systems and data collection pipelines.
    • Experience with NVIDIA Omniverse or sim-to-real workflows.
    • Experience with reinforcement learning frameworks or visuomotor policy training.
    • Experience working with dexterous hands or humanoid manipulation platforms.

Key Competencies

• Strong interest in robotics and embodied AI research.
• Able to build and maintain strong working relationships with internal and external stakeholders.
• Self-directed learner with strong initiative and ownership of work.
• Strong analytical and critical thinking skills.
• Proficient in technical writing and presentation.
• Able to work effectively in experimental and rapidly evolving research environments.