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/Lecturer-in-the-Department-of-Mechanical-Engineering/32835-en_GB/?st=CB79709B52026097E71D193CED0DFB2588730B63

We regret that only shortlisted candidates will be notified.

Job Description

The Department of Mechanical Engineering (ME) at the National University of Singapore (NUS) invites applications for a full-time Lecturer position in the area of Robotics and Machine Intelligence. This is an Educator Track position for individuals passionate about undergraduate and graduate teaching, student mentoring, curriculum development, and educational innovation.

This role supports the department’s key academic programmes, including:
•    The BEng (Robotics and Machine Intelligence) – an interdisciplinary direct honours programme hosted by NUS ME;
•    The BEng (Mechanical Engineering) – with a focus on control systems, mechatronics, and the robotics specialisation track;
•    The MSc (Robotics) – an applied graduate programme preparing students for advanced careers in intelligent automation and robotics industries.
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.