Program Overview

Engineering Science Programme

The Engineering Science Programme offers a multidisciplinary approach to engineering, combining physics, mathematics, and engineering principles to solve complex problems. The programme provides students with a strong foundation in engineering science, as well as the opportunity to specialize in a specific area of interest.

Specialisations

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

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

Nanoscience and Technology (NANO)

Nanoscience and Technology is a specialisation that 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.

Core Courses

• ESP3102 / PC3242: From Making Nano to Probing Nano / Nanofabrication and Nanocharacterization
• CM3296: Molecular Modelling: Theory and Practice

Elective Courses

• Group A: Choose one
  • EE4437: Photonics – Principles and Applications
  • PC3247: Modern Optics
  • PC3251: Nanophysics
  • PC4259: Surface Physics (Applies from Cohort 2017 onwards)
• Group B: Choose two
  • BN5101: Biomedical Engineering Systems (Not available from Aug 2022)
  • CM3231: Quantum Chemistry and Molecular Thermodynamics
  • CM3232: Physical Chemistry of the Solid State and Interfaces
  • CM3251: Nanochemistry
  • CM5223: Topics in Supramolecular Chemistry
  • EE3407: Analog Electronics
  • EE3408C: Integrated Analog Design
  • EE3431C: Microelectronics Materials and Devices
  • EE4436: Fabrication Process Technology
  • EE4509: Silicon Micro Systems
  • EE5431: Fundamentals of Nanoelectronics
  • EE5434: CMOS Processes and Integration
  • EE5439: Micro/Nano Electromechanical Systems
  • EE5440: Magnetic Data Storage for Big Data
  • EE5502: MOS Devices
  • EE5508: Semiconductor Fundamentals
  • PC3233: Atomic & Molecular Physics I
  • PC3235: Solid State Physics 1
  • PC3241: Solid State Devices
  • PC3274: Mathematical Methods in Physics II
  • PC4240: Solid State Physics 2
  • PC4253: Thin Film Technology
  • PC4274: Mathematical Methods in Physics III
  • PC5209: Accelerator Based Materials Characterization
  • PC5212: Physics of Nanostructures
  • PC5214: Principles of Experimental Physics
  • PC5247: Photonics II

Energy Science and Technology (ES)

Energy Science and Technology is a specialisation that 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.

Core Courses

• ME4252/ESP5403: Nanomaterials for Energy Engineering/ Nanomaterials for Energy Systems
• ESP5402: Transport Phenomena in Energy Systems

Elective Courses

• Group A: Choose three (Cohort 2017 onwards)
  • EE3506C: Electrical Energy Systems (RECOMMENDED)
  • EE4438: Solar Cells & Modules (Preclude: EE4432 Devices for Elect. Energy Gen.)
  • EE4501: Power System Management And Protection
  • EE4502: Electric Drives & Control
  • EE4511: Renewable Generation and Smart Grid
  • ESP3102 / PC3242: From Making Nano to Probing Nano / Nanofabrication and Nanocharacterization
  • ESP4401: Optimization of Energy System
  • ME3122: Heat Transfer
  • ME3221: Sustainable Energy Conversion
  • ME4223: Thermal Environmental Engineering
  • ME4225: Applied Heat Transfer
  • ME4226: Energy and Thermal Systems
  • ME4227: Internal Combustion Engines
  • ME5204: Air Conditioning and Building Automation
  • ME5205: Energy Engineering
  • ME5516: Emerging Energy Conversion and Storage Technologies

Computational Engineering Science (CES)

Computational Engineering Science is a specialisation that uses mathematics and physics to build computational models to solve scientific and engineering problems. Models may be created in computers (virtual models), that enables the design of engineering systems to perform a function.

Core Courses

• ESP4901: Research Project

Elective Courses

• Group A: Choose one from any of the below (Modelling and Simulation track)
  • ME4291: Finite Element Analysis
• Group A: Choose one from any of the below (Computational Robotics track)
  • ESP3201: Machine Learning in Robotics and Engineering
• Group B: Choose four (Cohort AY2017/18 onwards) from any of the below
  • BN5205: Computational Biomechanics
  • BT3102: Computational Methods for Business Analytics
  • CE4258: Structural Stability & Dynamics
  • CG3207: Computer Architecture
  • CM3296: Molecular Modelling: Theory and Practice
  • CN3421: Process Modelling & Numerical Simulation
  • CS3216: Software Product Engineering for Digital Markets
  • CS3243: Introduction to Artificial Intelligence
  • CS3244: Machine Learning
  • CS4243: Computer Vision and Pattern Recognition
  • EE3331C: Feedback Control Systems
  • EE4204: Computer Networks
  • EE4212: Computer Vision
  • EE4305: Fuzzy/Neural Systems for Intelligent Robotics
  • EE4308: Autonomous Robot Systems
  • EE4309: Robot Perception
  • EE5101: Linear Systems
  • EE5103: Computer Control Systems
  • EE5106: Advanced Robotics
  • EE5904: Neural Networks
  • ESP5402: Transport Phenomena in Energy Systems
  • MA3220: Ordinary Differential Equations
  • MA3227: Numerical Analysis II
  • MA3236: Non-Linear Programming
  • MA4230: Matrix Computation
  • MA4255: Numerical Methods in Differential Equations
  • MA5233: Computational Mathematics
  • ME4233: Computational Methods in Fluid Mechanics
  • ME4245: Robot Mechanics and Control
  • ME5302: Computational Fluid Mechanics
  • ME5361: Advanced Computational Fluid Dynamics
  • ME5402: Advanced Robotics
  • ME5404: Neural Networks
  • ME5405: Machine Vision
  • PC3236: Computational Methods in Physics
  • PC3274: Mathematical Methods in Physics II
  • PC4274: Mathematical Methods in Physics III

Engineering Science in Medicine (ESM)

Engineering Science in Medicine is a specialisation that aims to better align the programme to the government 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.

Core Courses

• PC3294: Radiation Lab
• ESP4901: Research Project

Elective Courses

• Group A: Choose one
  • EE4603: Biomedical Imaging Systems
  • BN4406: Biophotonics and Bioimaging
  • BN4201: Tissues Biomechanics
• Group B: Choose one
  • PC3232: Nuclear and Particle Physics
  • PC3232B: Applied Nuclear Physics
• Group C: Choose two (Cohort AY2017/18 onwards)
  • BN3202: Musculo-Skeletal Biomechanics
  • BN3301: Introduction to Biomaterials
  • BN3402: Bio-Analytical Methods in Bioengineering
  • BN4202: Biofluids Dynamics
  • BN4402: Electrophysiology
  • BN5101: Biomedical Engineering Systems (Not available from Aug 2022)
  • BN5102: Clinical Instrumentation (Not available from Aug 2022)
  • BN5205: Computational Biomechanics
  • BN5209: Neurosensors and Signal Processing
  • EE3331C: Feedback Control Systems
  • EE4704: Image Processing and Analytics
  • LSM3215: Neuronal Signalling and Memory Mechanisms
  • LSM3222: Human Neuroanatomy
  • LSM3242: Translation Microbiology
  • LSM3243: Molecular Biophysics
  • PC3243: Photonics
  • PC3247: Modern Optics
  • PC3267: Biophysics
  • PC3295: Radiation for Imaging and Therapy in medicine