Program Overview

Engineering Science Programme

The Engineering Science Programme offers a multidisciplinary approach to engineering, combining physics, electrical engineering, and other disciplines to provide students with a comprehensive understanding of engineering principles and practices.

Specialisations

The programme offers several specialisations, each with its own set of elective courses. The specialisations are:

• Nanoscience and Technology (NANO)
• Energy Science and Technology (EST)
• Computational Engineering Science (CES)
• Engineering Science in Medicine (ESM)

Nanoscience and Technology (NANO)

Nanoscience and Technology focuses on the understanding, design, fabrication, and testing of structures and materials at the nanometer scale. Students learn how controlling shape and size at the nanometer scale enables the design of smaller, lighter, faster, and better-performing materials, components, and systems. This specialisation combines both a physics and electrical engineering approach.

Elective Courses

Students must choose any five of the following elective courses:

• CM3296: Molecular Modelling: Theory and Practice
• EE3104C: Intro to RF and Microwave Systems & Circuits
• ESP3201: Machine Learning in Robotics and Engineering (recoded to ESP3201A)
• ESP3201A: Machine Learning in Engineering Science
• ME3252: Materials for Mechanical Engineering
• ME4252: Nanomaterials for Energy Engineering
• PC3232: Nuclear and Particle Physics
• PC3233: Atomic & Molecular Physics I
• PC3242: Nanofabrication and Nanocharacterization (offered every alternate AY starting from AY2026/2027)
• PC3243: Photonics
• PC3247: Modern Optics
• PC3251: Nanophysics
• PC4240: Solid State Physics 2
• PC4253: Thin Film Technology
• PC4259: Surface Physics

Energy Science and Technology (EST)

Energy Science and Technology provides a multidisciplinary understanding of production and conversion of various forms of energy. It addresses non-renewable as well as renewable energy sources. Students learn to tackle some of the most pressing problems we face today in terms of energy generation, storage, and management.

Elective Courses

Students must choose any five of the following elective courses:

• EE2022: Electrical Energy Systems
• EE4501: Power System Management And Protection
• EE4503: Power Electronics for Sustainable Energy Technologies
• EE4511: Renewable Generation and Smart Grid
• EE4513: Electric Vehicles and their Grid Integration
• ESP3201: Machine Learning in Robotics and Engineering (recoded to ESP3201A)
• ESP3201A: Machine Learning in Engineering Science
• ESP4401: Optimization of Energy System
• ESP5402 / ESP4403: Transport Phenomena in Energy Systems (offered every alternate AY starting from AY2025/2026)
• ME3122: Heat Transfer
• ME3221: Sustainable Energy Conversion (no longer offered from AY2025/2026)
• ME4223: Thermal Environmental Engineering
• ME4225: Applied Heat Transfer (no longer offered from AY2024/2025)
• ME4226: Energy and Thermal Systems
• ME4227: Internal Combustion Engines
• ME4252: Nanomaterials for Energy Engineering
• PC3242: Nanofabrication and Nanocharacterization

Computational Engineering Science (CES)

Computational Engineering Science uses mathematics and physics to build computational models to solve scientific and engineering problems. Models may be created in computers (virtual models), which enables the design of engineering systems to perform a function. Such virtual models guide the design and creation of engineering products like automobiles, airplanes, energy systems, etc. This specialisation also gives the opportunity to discover assorted computational aspects associated with robotics and artificial intelligence.

Elective Courses

Students must choose any five of the following elective courses:

• CM3296: Molecular Modelling: Theory and Practice
• EE3331C: Feedback Control Systems
• EE4212: Computer Vision
• EE4305: Fuzzy/Neural Systems for Intelligent Robotics (no longer offered from AY2024/2025)
• EE4307: Control Systems Design and Simulation
• EE4308: Autonomous Robot Systems
• EE4309: Robot Perception
• EE4311: Fuzzy Logic and Neuro Fuzzy Systems
• EE4312: Artificial Neural Networks
• EE4704: Image Processing and Analysis
• EE4705: Human Robot Interaction
• ESP3201: Machine Learning in Robotics and Engineering (recoded to ESP3201A)
• ESP3201A: Machine Learning in Engineering Science
• ESP5402/ESP4403: Transport Phenomena in Energy Systems
• MA3236: Non-Linear Programming
• MA3252: Linear and Network Optimisation
• MA3264: Mathematical Modelling
• MA4254: Discrete Optimisation
• ME4233: Computational Methods in Fluid Mechanics
• ME4245: Robot Mechanics and Control
• ME4291: Finite Element Analysis

Engineering Science in Medicine (ESM)

This specialisation aims to better align the programme with the government's RIE2020 plans, where healthcare is cited as a major requirement for the future of Singapore. Engineering in Medicine is also one of six major research themes selected by the College of Design and Engineering at NUS that is encouraged and supported for research. The Engineering Science topic is naturally present in many state-of-the-art instruments in the healthcare industry.

Elective Courses

Students must choose any five of the following elective courses:

• BN3202: MusculoSkeletal Biomechanics
• BN3402: Bio-Analytical Methods in Bioengineering
• BN4202: Biofluids Dynamics
• EE3331C: Feedback Control Systems
• EE4704: Image Processing and Analysis
• EE4705: Human Robot Interaction
• ESP3201: Machine Learning in Robotics and Engineering (recoded to ESP3201A)
• ESP3201A: Machine Learning in Engineering Science
• ME3281: Microsystems Design And Applications
• ME4253: Biomaterials Engineering
• PC3232: Nuclear and Particle Physics
• PC3243: Photonics
• PC3247: Modern Optics
• PC3267: Biophysics
• PC3294: Radiation Labatory
• PC3295: Radiation for Imaging and Therapy in medicine

The Engineering Science Programme is offered by the College of Design and Engineering at the National University of Singapore. The programme's address is 9 Engineering Drive 1, Block EA #07-08, Singapore.