The School of Mechanical & Aerospace Engineering (MAE) is a robust, dynamic and multi-disciplinary international research community comprising of world-class scientists and bright students. MAE prides itself in its excellent research capabilities in areas including advanced manufacturing, aerospace, biomedical, energy, industrial engineering, maritime engineering, robotics, etc. The school is equipped with state-of-the-art research infrastructure, housing a comprehensive range of cluster laboratories, test bedding facilities, research centres/institutes and corporate laboratories. Cutting-edge research in MAE addresses the immediate needs of our industries and supports the nation’s long-term development strategies. In the new era of industrial 4.0 and sustainable living, MAE is rigorous in developing new competencies to support the growth and competitiveness of our engineering sector in the global landscape. MAE has grown to be leader in Engineering Research, ranking amongst the top engineering schools in the world.

For more details, please view https://www.ntu.edu.sg/mae/research.

We are looking for a Research Engineer in Autonomous Drone Swarms for GPS-Denied Environments to develop and integrate the hardware and software required for coordinated multirotor operations in complex, cluttered environments. The role will focus on designing and implementing onboard sensing, communication, computing, localisation, navigation, and control systems for autonomous drone swarms operating without reliable GPS. The Research Engineer will also develop and validate swarm coordination, collaborative perception, mapping, obstacle avoidance, and multi-agent path-planning algorithms, and integrate these capabilities on physical drone platforms. The work will involve system integration, simulation, hardware-in-the-loop testing, flight experimentation, and performance evaluation under realistic GPS-denied conditions.

Key Responsibilities:

• Develop and integrate hardware and software architectures for autonomous multirotor drone swarms operating in GPS-denied and 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.

• Conduct simulation, hardware-in-the-loop testing, system integration, and flight experiments to evaluate robustness, scalability, and performance under realistic operating conditions.

• Work with researchers and project collaborators to support system demonstrations and prepare technical reports, publications, project deliverables, and documentation.

Job Requirements:

Education qualifications

• Bachelor’s or Master’s degree in Aerospace Engineering, Electrical and Electronic Engineering, Mechanical Engineering, Computer Engineering, Robotics, Computer Science, or a closely related discipline.

• Strong academic or project background in autonomous systems, robotics, unmanned aerial vehicles, embedded systems, or multi-agent systems.

• Research or project experience in autonomous drone navigation, drone swarms, or GPS-denied operations would be advantageous.

Soft skills

• Strong communication, analytical, and problem-solving skills.

• Strong sense of ownership, responsibility, and initiative.

• Ability to work effectively with researchers, engineers, students, industry partners, and project stakeholders.

• Willingness to support flight testing, system demonstrations, project reporting, and milestone reviews.

Hard skills

• Demonstrated hands-on experience in the hardware and software integration of autonomous robots or multirotor drones.

• Proficiency in C++, Python, MATLAB, or equivalent programming languages for robotics and autonomous-system development.

• Experience with robotic middleware and simulation environments such as ROS/ROS 2, Gazebo, AirSim, or equivalent platforms.

• Experience integrating sensors, embedded computers, communication modules, flight controllers, and other onboard hardware.

• Familiarity with autopilot platforms such as PX4 or ArduPilot and communication protocols such as MAVLink would be advantageous.

• Knowledge of localisation, visual-inertial odometry, simultaneous localisation and mapping, obstacle avoidance, path planning, and flight-control algorithms.

• Familiarity with multi-agent coordination, task allocation, formation control, collaborative perception, or distributed swarm algorithms would be advantageous.

Experience

• Experience integrating sensing, localisation, navigation, communication, control, and decision-making components within a robotics or autonomous-drone project.

• Practical experience assembling, configuring, troubleshooting, and flight-testing multirotor platforms would be highly advantageous.

Competencies

• Ability to independently design, integrate, test, and troubleshoot autonomous-drone hardware and software systems.

• Ability to work across robotics, embedded systems, perception, navigation, control, and multi-agent coordination domains.

• Ability to conduct systematic experiments and evaluate system performance, robustness, scalability, and reliability.

• Ability to deliver research outcomes within project timelines and contribute to technical reports, project demonstrations, and high-quality publications.

We regret to inform that only shortlisted candidates will be notified.