Established in 2010, the Energy Research Institute @ NTU (ERI@N) is a pan-university research institute that focuses on systems-level research for tropical megacities. It performs translational research that covers the energy value chain from generation to innovative end-use solutions, motivated by industrialisation and deployment. ERI@N has multiple Interdisciplinary Research Programmes which focus on translational Research, Development & Deployment which focus on specific area of the energy value chain, and a number of Living labs and Testbeds which facilitate large scale technology deployment enabling validation and demonstration of real-world applications.
For more details, please view
https://www.ntu.edu.sg/erian
Our department is seeking to hire a software engineer with experience in C++, Python, and Linux systems to join the Future Mobility Solutions research program. The successful candidate will work on the development, testing, and fine-tuning of self-driving vehicles, ranging from utility vehicles like buggies and road sweepers to public road vehicles. This role will contribute to advancing the autonomous driving technologies and robotics by supporting software development, vehicle trials and data processing.

Key Responsibilities:

• Work on C++ and Python codes for software development in linux systems
• Added advantage if familiar with ROS or ROS2 for building autonomous or robotics systems
• Beneficial if familiar with open-source platforms like Autoware or Apollo for self-driving systems
• Develop, test, and fine-tune software for autonomous robots and vehicles across different platforms.
• Process and analyze sensor data, including LIDAR and camera inputs, for robotics and automation applications.
• Conduct outdoor vehicle trials for testing and validation of perception, navigation algorithms, and self-driving systems.
• Collaborate with team on improving and optimizing the performance of the autonomous vehicle system for real-world conditions.
• Participate in vehicle data collection activities and help refine software to meet project deliverables.
• Engage in software development and troubleshooting using ROS/ROS2 frameworks.
• Work on implementing object recognition and tracking models, such as YOLO, including optimizing model performance with tools like TensorRT
• Implement object recognition and tracking models, such as YOLO or similar frameworks, and integrate them into the existing autonomous software stack to enhance path planning and navigation, ensuring improved decision-making and obstacle avoidance.

Job Requirements:

• Minimum Knowledge and Skills: Proficient in C++, Python, and Linux systems
• Beneficial Experience:
• Strong understanding of LIDAR and camera sensor data processing for robotics and automation (and other sensors such as RADARs and Ultra-sonic sensors).
• Familiar with ROS or ROS2 environments.
• Experience with outdoor testing, data collection, and validation of algorithms used in self-driving applications such as perception and navigation algorithms.
• Prior work on open-source autonomous driving platforms such as Autoware or Apollo.
• Familiarity with computer vision and experience implementing image / object recognition systems, such as YOLO, for real-time object detection and classification.
• Background in robotics and automation.
• Education: Bachelor’s or Master’s degree in Computer Science, Robotics, Automation, or a related field.

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

• Work on C++ and Python codes for software development in linux systems
• Added advantage if familiar with ROS or ROS2 for building autonomous or robotics systems
• Beneficial if familiar with open-source platforms like Autoware or Apollo for self-driving systems
• Develop, test, and fine-tune software for autonomous robots and vehicles across different platforms.
• Process and analyze sensor data, including LIDAR and camera inputs, for robotics and automation applications.
• Conduct outdoor vehicle trials for testing and validation of perception, navigation algorithms, and self-driving systems.
• Collaborate with team on improving and optimizing the performance of the autonomous vehicle system for real-world conditions.
• Participate in vehicle data collection activities and help refine software to meet project deliverables.
• Engage in software development and troubleshooting using ROS/ROS2 frameworks.
• Work on implementing object recognition and tracking models, such as YOLO, including optimizing model performance with tools like TensorRT
• Implement object recognition and tracking models, such as YOLO or similar frameworks, and integrate them into the existing autonomous software stack to enhance path planning and navigation, ensuring improved decision-making and obstacle avoidance