Research Fellow (Unmanned Systems, Multi-Agent Robot System)

Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal. NUS Career Portal link - https://careers.nus.edu.sg/job/Research-Fellow-%28Unmanned-Systems%2C-Multi-Agent-Robot-System%29/33938-en_GB/ We regret that only shortlisted candidates will be notified. Job Description We are seeking a highly motivated and experienced Research Fellow to join an exciting research project on Counter-Unmanned Aerial Systems (C-UAS). The successful candidate will lead cutting-edge research in autonomous robotic systems for detecting, tracking, and intercepting hostile unmanned aerial vehicles (UAVs). The position involves close collaboration with the Principal Investigator (PI), multidisciplinary research teams, and local and international collaborators to develop next-generation autonomous C-UAS technologies. Key Responsibilities • Lead and conduct high-quality research in Counter-Unmanned Aerial Systems (C-UAS), autonomous robotics, and multi-agent systems. • Develop novel algorithms for autonomous target detection, recognition, tracking, localization, threat assessment, and aerial interception of hostile UAVs. • Conduct research on multi-agent and heterogeneous robotic systems involving UAVs, UGVs, USVs, and other autonomous platforms, including task allocation, cooperative planning, swarm intelligence, and distributed decision-making. • Design and implement software solutions in Python and/or C++, including algorithm development, optimization, and deployment on embedded computing platforms. • Integrate software with robotic hardware, including UAV platforms, flight controllers, cameras, vision sensors, communication systems, and other onboard sensors. • Lead simulation studies, hardware integration, laboratory experiments, and outdoor flight testing to validate developed technologies. • Supervise and mentor Research Engineers, Research Assistants, graduate students, and visiting researchers. • Publish high-quality research findings in leading international journals and conferences and contribute to intellectual property development where appropriate. • Prepare technical reports, project documentation, milestone deliverables, and presentations for project sponsors and collaborators. • Support the PI in project management, research planning, funding proposals, and coordination with local and international research partners. • Perform other research-related duties assigned by the PI in support of the C-UAS project. Qualifications Qualifications • PhD in Aerospace Engineering, Robotics, Mechanical Engineering, Electrical Engineering, Computer Science, Artificial Intelligence, or a closely related discipline. • Strong background in autonomous robotic systems, unmanned aerial systems (UAS), or multi-agent robotics. • Demonstrated expertise in one or more of the following areas: o Counter-UAS technologies o Multi-agent systems and swarm robotics o Autonomous navigation and guidance o Computer vision and perception o Machine learning or reinforcement learning o Sensor fusion and state estimation o Motion planning and control • Excellent programming skills in Python and/or C++. • Experience with ROS/ROS 2, Linux, Git, and robotic software development. • Hands-on experience integrating robotic software with UAV hardware, cameras, embedded computing platforms (e.g., NVIDIA Jetson), and flight control systems. • Strong publication record in reputable international journals and conferences relevant to robotics, UAVs, autonomous systems, or artificial intelligence. • Demonstrated ability to independently lead research projects and supervise junior researchers and graduate students. • Excellent communication and scientific writing skills in English. • Experience in collaborative research with industry, government agencies, or international partners is an advantage. Required Skills • Experience with PX4 or ArduPilot flight control systems. • Knowledge of UAV communication systems and embedded AI. • Experience with simulation environments such as Gazebo, AirSim, Isaac Sim, or MATLAB/Simulink. • Experience in optimization, distributed control, multi-agent reinforcement learning, or mission planning. • Familiarity with real-time robotic systems and hardware-in-the-loop testing. • Experience managing externally funded research projects is desirable. • Familiarity with or hands-on experience in UAVs (drones), opto-electronic systems (e.g., cameras and vision sensors), robotic systems, and autonomous platforms.