Deskripsi Pekerjaan
Join the cutting-edge research team at Nanyang Technological University (NTU) as a Research Fellow specializing in Multi-Sensor Fusion. We are seeking a highly motivated individual to contribute to the development of advanced localization and perception systems for next-generation robotics. In this pivotal role, you will design and implement robust fusion algorithms capable of operating effectively in complex, unstructured environments. You will work with state-of-the-art sensor suites, including LiDAR, Radar, and Cameras, to create seamless perception pipelines that drive autonomous navigation.
As a Research Fellow, you will collaborate closely with a multidisciplinary team of engineers and researchers to solve challenging problems in robotics. Your work will directly impact the field of autonomous systems, ensuring that machines can perceive and understand their surroundings with high accuracy. We are looking for someone who is passionate about algorithm development, possesses a strong theoretical foundation, and is eager to push the boundaries of what is possible in robotic perception.
Tanggung Jawab
- Design, implement, and optimize multi-sensor fusion algorithms for autonomous navigation.
- Develop advanced localization techniques to estimate the precise pose of robotic platforms in dynamic environments.
- Process and fuse heterogeneous data streams from LiDAR, Radar, and Camera sensors.
- Collaborate with cross-functional teams to integrate perception modules into robotic systems.
- Analyze system performance and debug complex issues in real-time perception pipelines.
- Contribute to the publication of research findings in top-tier academic conferences and journals.
- Conduct experiments and validate algorithms using simulation tools and real-world datasets.
Kualifikasi
- Ph.D. or Master’s degree in Robotics, Computer Science, Electrical Engineering, or a related field (or equivalent industrial experience).
- Strong background in sensor fusion, Kalman filters, Particle Filters, or Deep Learning-based fusion methods.
- Proven experience with point cloud processing, stereo vision, or radar signal processing.
- Proficiency in programming languages such as C++ and Python.
- Familiarity with robotic frameworks (e.g., ROS/ROS2) and simulation tools (e.g., Gazebo, CARLA).
- Excellent problem-solving skills and the ability to work independently on complex technical challenges.