Research Engineer I - Autonomous Drone Swarm

About the role

The School of Mechanical & Aerospace Engineering at NTU is looking for a Research Engineer to develop and integrate the hardware and software needed for coordinated multirotor operations in complex, cluttered environments without reliable GPS. The work covers onboard sensing, communication, computing, localisation, navigation and control, as well as swarm coordination, collaborative perception, mapping, obstacle avoidance and multi-agent path planning, validated through simulation, hardware-in-the-loop testing and flight experiments.

Key responsibilities

• Develop and integrate hardware and software architectures for autonomous multirotor drone swarms in GPS-denied, cluttered environments.
• Design and implement onboard sensing, localisation, mapping, navigation, obstacle avoidance, communication and flight-control systems.
• Develop swarm coordination, task allocation, multi-agent path planning, collaborative perception and inter-drone information-sharing algorithms.
• Run simulations, hardware-in-the-loop tests, system integration and flight experiments to evaluate robustness, scalability and performance.
• Work with researchers and collaborators on demonstrations, technical reports, publications, project deliverables and documentation.

Required profile

• Bachelor's or Master's degree in Aerospace, Electrical and Electronic, Mechanical, Computer, Robotics or Computer Science engineering, or a closely related discipline.
• Strong academic or project background in autonomous systems, robotics, UAVs, embedded systems or multi-agent systems.
• Experience in autonomous drone navigation, swarms or GPS-denied operations is advantageous.
• Hands-on experience integrating sensing, localisation, navigation, communication, control and decision-making in a robotics or autonomous-drone project.
• Practical experience assembling, configuring, troubleshooting and flight-testing multirotor platforms is highly advantageous.

Required skills

• C++, Python, MATLAB or equivalent for robotics and autonomous-system development.
• ROS/ROS 2, Gazebo, AirSim or similar simulation platforms.
• Integration of sensors, embedded computers, communication modules, flight controllers and onboard hardware.
• Advantageous: PX4 or ArduPilot autopilots, MAVLink, visual-inertial odometry, SLAM, obstacle avoidance, path planning, formation control and distributed swarm algorithms.