Senior Lecturer

1 week ago

Singapur, Singapore National University of Singapore Full time

Overview The Department of Mechanical Engineering (ME) at the National University of Singapore (NUS) invites applications for a full-time Senior Lecturer position in Robotics and Machine Intelligence. This Educator Track position focuses on undergraduate and graduate teaching, student mentoring, curriculum development, and educational innovation. Key Responsibilities Deliver undergraduate and postgraduate modules in areas such as Fundamentals of Robotics; Control Systems and Mechatronics; AI and Machine Learning for Robotics; Embedded Systems and Intelligent Sensors; Robot Perception and Decision-Making. Contribute to the design, review, and refinement of curricula across BEng (RMI), BEng (ME), and MSc (Robotics). Develop and supervise hands-on, project-based learning activities, including capstone projects, laboratory modules, and industry-linked challenges. Mentor undergraduate and graduate students on academic development, design projects, and professional pathways. Guide student teams participating in competitions, start-up ventures, or applied R&D. Pioneer new instructional approaches including flipped classrooms, experiential learning, and interdisciplinary integration. Participate in university- and faculty-level teaching committees, curriculum review panels, and digital education initiatives. Qualifications Essential: A PhD degree in Robotics, Mechanical Engineering, Electrical & Computer Engineering, Mechatronics, or related disciplines. Demonstrated excellence (or strong potential) in undergraduate and/or graduate-level teaching, particularly in robotics, control systems, and intelligent automation. Strong foundation in programming and systems integration (e.g., C/C++, Python, ROS, MATLAB/Simulink, microcontrollers). Familiarity with modern AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and their integration with robotic platforms. Preferred: Experience in teaching multi-disciplinary cohorts, or designing and delivering project-based learning. Proven experience or demonstrated potential in applying AI and machine learning techniques to robotics, control, or automation systems. Research background that bridges robotics and intelligent systems, such as autonomous systems, reinforcement learning, perception, or cognitive robotics. Familiarity with industry-grade robotic platforms, simulation environments, and machine learning toolkits. Exposure to industrial applications of robotics (e.g., AMRs, industrial automation, assistive robotics) is a plus. Experience supervising FYPs, MSc theses, or leading capstone courses. More Information Location: Kent Ridge Campus Organization: College of Design and Engineering Department: Mechanical Engineering Employee Referral Eligible: No Job requisition ID: 30070 Details Seniority level: Not Applicable Employment type: Full-time Job function: Education and Training Industries: Higher Education, Education Administration Programs, and Strategic Management Services #J-18808-Ljbffr

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