NTU’s MSc (Robotics & Intelligent Systems) blends theory and hands-on practice for roles in robotics engineering, automation, intelligent systems, and R&D, with strong local and international prospects. Aligned with Singapore’s Smart Nation 2.0 and RIE 2030, it supports manufacturing, health, urban solutions, and the digital economy. Enables sustainable growth and digital manufacturing, expanding opportunities in the precision engineering ecosystem.

MAE features top faculty in Autonomous Systems, Embodied Intelligence, BioRobotics, Rehabilitation Engineering, Smart Mobility, Robotic Microsurgery, Robotic Materials, and Human–Robot Interaction, pursuing translational R&D for maximal impact through the Robotics Research Centre (RRC).

Graduates may join leading companies and research institutions, driving innovation locally and globally.

Admission Information

Admissions Application period for August 2026 intake will be from 1 November 2025 to 31 March 2026.

- MAE at NTU blends robotics expertise with a culture of innovation. Faculty lead research across:
Autonomous Systems, Embodied Intelligence, BioRobotics Rehabilitation Engineering, Smart Mobility, Robotic Microsurgery Robotic Materials, Human–Machine Interaction.

- Collaborative culture: interdisciplinary projects, industry partnerships, venture opportunities, real-world impact.
Students access NTU’s research ecosystem, notably: Robotics Research Centre (RRC): Singapore’s first interdisciplinary robotics center. (est. 1994)

- Hands-on learning, translational projects, internships, startup/funding pathways.

- Translational impact: lab-to-market through partnerships, startups, and government initiatives.

-Global Excellence in Energy Research and Singapore as a Living Laboratory converge in this MSc.

- Strong mechanical engineering core with interdisciplinary reach and industry-driven projects.

- Graduates pursue R&D, policy, and energy management roles.

- Industry collaborations and real-world projects prepare leaders for the global clean energy transition.

- Enables versatile careers across engineering, sustainability, and technology innovation.

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Option to pursue a dissertation project in lieu of two courses

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MAE Graduate Scholarship

The MAE Graduate Scholarship is awarded to exceptional applicants applying for admission to MAE's Master of Science programmes.

The applicant must be able to demonstrate significant potential to enhance the academic rigor and reputation of the programme.

On top of the admission requirements of each programme, applicants will be assessed based on multiple factors that include academic record, working experiences, past achievements and awards, etc.

Shortlisted applicants may be invited for interviews, and successful applicants will be informed of the outcome shortly after the offer of admission.

Each Scholarship amounts to 100% of the total Tuition Fees for the programme, not including miscellaneous fees. The amount cannot be used to offset the SGD50 application fee and the SGD5000 acceptance of offer deposit payment.

Partial scholarships (50% of the total tuition fees) may also be awarded at the discretion of the Scholarship Evaluation Committee.

Recipients are expected to maintain a CGPA of 3.50 each Semester to maintain the eligibility for the Scholarship.

If you are interested, please complete and submit the MAE Graduate Scholarship Application Form to MAE Graduate Studies Office ([email protected]). Deadline for submission 31 March 2026.

Candidates must possess

(A) A good bachelor’s degree in engineering, such as Aerospace, Mechanical or Electrical Engineering.

(B) A good TOEFL score (iBT = 85 or more, PBT = 563 or more, CBT = 223 or more) or IELTS score (6.0 or more) for graduates of universities in which English is not the medium of instruction. Please ensure that you upload a scanned copy of TOEFL/IELTS along with your application (hardcopy is not required).

Related disciplines include but are not limited to bachelor's programmes offered by the College of Engineering, Nanyang Technological University, Singapore.

Applicants must also provide 2 letters of reference from academic or professional supervisors and a clear statement of purpose in support of their application.

Full-Time (min. 1 year, max. 2 years) and Part-Time (min. 2 years, max. 4 years);

30 AUs coursework or 24 AUs coursework and a dissertation

Option	Description	No. of Courses	Core	Prescribed/ Specialised Electives^	Electives^
1	Coursework and Dissertation^#	8 Courses + Dissertation	2	(Group A) Min: 3 Max: 5	(Group B) Min: 1 Max: 3
2	Coursework Only (*Default Option)	10 Courses	2	(Group A) Min: 3 Max: 5	(Group B) Min: 2 Max: 4 (Group C) Min: 1 Max: 1

^#Full-time students choosing the dissertation option typically require 1.5 years instead of 1 year to graduate.

^For Group A, B and C Electives, refer to Curriculum for more information.

*Please note that ALL students will automatically be assigned the default Option 2 - Coursework Only. If
you wish to apply for Option 1: Coursework and Dissertation, you must apply using the "Application for
Conversion of Option of study" form during your first Semester.

CORE COURSES

Course Code	Title	AUs
MA6210	Introduction to Advanced Robotics and Autonomous Systems	3
MA6217	Computational Methods in Robotics	3

GROUP A ELECTIVE COURSES (PRESCRIBED ELECTIVES)

Course Code	Title	AUs
MA6211	AI and Machine Learning Fundamentals for Robotics	3
MA6212	Robotics Manipulation and Advanced Control	3
MA6213	Sensors and Data Fusion	3
MA6214	Autonomous Mobile Robot	3
MA6216	Vision	3

GROUP B ELECTIVE COURSES (GENERAL ELECTIVES)

Course Code	Title	AUs

MA6223	Medical and Healthcare Robotics	3
MA6224	Unmanned Vehicles	3
MA6501	Manufacturing Control and Automation	3
MA7220	Metaverse and Digital Twin	3
MA7223	Human-Robot Interaction	3

GROUP C ELECTIVE COURSE (Applied Research and Learning - PRACTICUM FOR ‘COURSEWORK ONLY’ STUDENTS)

Course Code	Title	AUs
MA6215	Robotics Projects	3

COURSE SYNOPSIS

Core Courses

MA6210 Introduction to Advanced Robotics and Autonomous Systems

This course will introduce students state-of-the art robotic and autonomous systems their real-world applications. The course would cover the fundamental robotic technologies, medical and healthcare robotics,

service and field robotics, wearable robots, micro/nano robotics, soft robotics, artificial intelligence, metaverse and advanced robotic technology for manufacturing and the ambient technology such as new actuators and sensors for robots. Societal impacts and ethical issues of robot deployment will be discussed, including both the positive and negative aspects.

MA6217 Computational Methods in Robotics

This course introduces you to numerical and computational techniques essential for solving real-world problems in robotics. You will learn how to implement stable and efficient algorithms for kinematics, dynamics, perception, control, and planning. Whether you aim to build intelligent robotic systems or analyze complex robot behaviors, this course equips you with the numerical foundations to tackle core robotics problems using modern computational tools. This course is ideal for graduate students in robotics, mechanical engineering, or related fields with an interest in algorithms, simulation, or autonomous systems.

Group A Electives (Prescribed Electives)

MA6211 AI and Machine Learning Fundamentals for Robotics

This course introduces Machine intelligence that allows robots to make decisions and learn from data without being programmed explicitly. This course introduces the fundamentals of AI and Machine Learning (ML) with a focus in real-world robotics applications. The course covers basic and advanced concepts in data analytics, logical frameworks, decision making, reasoning, and prediction methodologies using AI and ML techniques specifically for the development and application of robots.

MA6212 Robotics Manipulation and Advanced Control

This course introduces Math background on rigid body motion based on geometric principle, Manipulator kinematics: forward, inverse and Jacobians, Robot dynamics and control, Manipulator motion & trajectory planning, multi-finger hand kinematics & grasping, and trending topics in robotics.

MA6213 Sensors and Data Fusion

This course introduces both the hardware and software components of sensors and their applications in the field

of robotics and automation. The first part of the course gives a comprehensive introduction of the fundamental

principles of sensor technologies, and the interfacing techniques with microcontrollers and computers. The second part covers sensing techniques such as signal processing and filtering, classical sensor fusion algorithms

and AI-based data fusion methods, with reference to a range of common robotic applications.

MA6214 Autonomous Mobile Robot

This course introduces the essential topics of mobile robotics such as advanced navigation algorithms, advanced path planning and motion controls, and multi-modal sensor fusion and localization techniques. It offers an in-depth exploration of diverse mobile robot types, including wheeled, legged, aerial, and aquatic models. Additionally, contemporary subjects in related areas, such as including swarm robotics, cooperative multi-robot systems, and the application of artificial intelligence in robot path planning and motion control, and ethics, safety, and regulatory considerations will be introduced.

MA6216 Vision

This course introduces the fundamentals of computer vision and image processing, and the application of these

techniques in robotics. The content covers a review of the relevant mathematical concepts, image representation

and colour space, object detection, classification and segmentation, and vision-based robot control techniques.

The students shall learn to implement computer vision techniques to provide perceptions to robots in real-world

applications such as manufacturing, navigation, and human-robot collaboration.

Group B Elective (General Electives)

MA6223 Medical and Healthcare Robotics

This course introduces the design, development, control and simulation of robots for medical and healthcare

applications such as surgery, rehabilitation and assisted living. It also examines the pain points of the

current healthcare system and the application of robotic solutions to address these issues. Ethical and

regulatory requirements in the development and deployment of medical robots shall also be discussed.

MA6224 Unmanned Vehicles

This course introduces the basic principles of UAV including aerodynamics, actuators & control, sensing &

sensors, and planning & navigation. Advanced topics covering the state-of-the-art UAV technologies such as

artificial intelligence, remote sensing, swarming and cooperative control will also be discussed. The students

will participate in practical projects to gain hands-on experience on the tools to integrate and implement a flying

model.

MA6501 Manufacturing Control and Automation

This course introduces an understanding of the technology of manufacturing automation, the common manufacturing processing, mathematical modeling of manufacturing process, the sensors to measure process output variables, the actuators available on machines and the control systems that enable operation of machines. The course covers the following topics: Manufacturing process modeling; Automation technology: robots; Automation Technology: machines; Robotic control; Machine control.

MA7220 Metaverse and Digital Twin

The first part of the course introduces the component technologies associated with Metaverse, which

include the Virtual Reality Continuum concept with Augmented Reality (AR), Mixed Reality, Augmented

Virtuality (AV), or even Real Virtuality (RV, or 3D Printing) and their industry applications. The second part of the course focuses on digital twin technology for robotics applications. It will cover fundamentals of physics-based simulator, Real2Sim process of performing system identifications to create a robot digital twin, model-based and learning based

controller design in simulations and Sim2Real process to validate and transfer simulation outcome to robots in the real world.

MA7223 Human-Robot Interaction

This course introduces students with a comprehensive understanding of the principles, techniques, and challenges associated with designing, developing, and evaluating robotic systems that interact and collaborate with humans in industrial, social, and healthcare contexts. Advanced topics such as Robotics Foundation Models and Human-in-the-loop robotics control will also be introduced. Students will gain knowledge and hands-on experience in physical and nonphysical (e.g. gesture, verbal, etc.) human-robot interfaces to interact and collaborate with industrial and service

robots.

Group C Elective (Applied Research and Learning - Practicum for 'Coursework-only' students)

MA6215 Robotics Projects

This course introduces students to gain hands-on skills and experience by working on robotics projects. The students will be working on individual or group projects that spanned the full spectrum of robotics technologies and applications, under the supervision of faculty members. A report will be submitted, followed by a presentation at the end of the semester.

Ideal for those with engineering, computer science, or related backgrounds pursuing robotics, automation, and intelligent systems. Builds local and international career paths in robotics-focused roles.

Career sectors: advanced manufacturing, healthcare, intelligent transportation systems, smart cities.

Additional avenues: startups/entrepreneurship and robotics education/outreach.

Fees

Please note this MSc programme is a self-financed, non-MOE subsidised programme.

		S$
Application Fees (Inclusive of 9% GST)	Non-Refundable (payable when you submit your application)	50
Deposit Payment (Inclusive of 9% GST)	Non-Refundable and non-transferable (Payable upon acceptance of offer of admission) The deposit will be used to offset tuition fees after matriculation	5,000
Tuition Fees – Academic Year 2026 – 2027 (Inclusive of 9% GST)	To attain an MSc in Robotic & Intelligent Systems, candidates must complete ten courses (30 AUs), or eight courses (24 Aus) and one dissertation (6 AUs)	56,682.18 (Full Programme) 1,889.41 (Per Academic Unit)

Fees are subject to annual revision.

Notes on payment of fees:
Students will be billed after course registration period each Semester, and payment due date is 2 weeks after billing date.
A student who withdraws or leaves the University after course registration period is liable to pay the fees due for the semester.
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Incentives for NTU Alumni

From AY2024-2025 intakes onwards: NTU Alumni students are entitled to 10% study incentives in the form of reduction in fees.

Incentives for Singapore Citizens and Singapore Permanent Residents

From AY2025-2026 intakes onwards: The $5,000 subsidy for Singapore Citizens and Permanent Residents will continue. Additionally, the maximum financial aid available for eligible local students will increase to $10,000. This enhancement applies only to new intakes from AY2025 onwards.

SkillsFuture Credits

If you are a Singaporean student, you may use up to $5000 of your SkillsFuture credits towards tuition fees. The claim submission has to be completed within 60 days of the start date of the next Semester (e.g. You must submit from November to claim towards Semester 2 tuition fees)

To do so, please follow the following steps:

Log in to SkillsFuture portal and click on “Make SkillsFuture Credit Claim.
Select NTU MSc Robotics and Intelligent Systems.
To submit a claim, you should have supporting documents such as letter of offer, matriculation documents etc.
In your claim, indicate the course start date to be first day of the upcoming Semester in the Academic Calendar.
As your e-bill for the upcoming Semester would not be available yet, take note of your SFC Claim ID.
Notify School ([email protected]) and NTU NSS-Finance ([email protected]) with the SFC Claim ID and theamount to be claimed through SFC.
When you receive your e-bill for the Semester, leave the SFC amount to be claimed out of your payment.
Please refer to Skillsfuture FAQ at this link.

Master of Science (Robotics and Intelligent Systems)