AY2021 & AY2022 & AY2023 Cohort

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 specialization combines both a physics and electrical engineering approach.

Elective Courses (Choose any FIVE)

CM3296 Molecular Modelling : Theory and Practice
EE3104C Intro to RF and Microwave Systems & Circuits
ESP3201 Machine Learning in Robotics and Engineering
ME4252 Nanomaterials for Energy Engineering
PC3232 Nuclear and Particle Physics
PC3233 Atomic & Molecular Physics I
PC3242 Nanofabrication and Nanocharacterization
PC3243 Photonics
PC3247 Modern Optics
PC3251 Nanophysics
PC4240 Solid State Physics 2
PC4253 Thin Film Technology
PC4259 Surface Physics

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 (Choose any FIVE)

EE4513 Electric Vehicles and their Grid Integration
ESP3201 Machine Learning in Robotics and Engineering
ESP5402 Transport Phenomena in Energy Systems
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
ME4252 Nanomaterials for Energy Engineering
PC3242 Nanofabrication and Nanocharacterization

Using 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. Such virtual models guide the design and creation of engineering products like automobiles, airplanes, energy systems, etc. This specialization also gives the opportunity to discover assorted computational aspects associated with robotics and artificial intelligence.

Elective Courses (Choose any FIVE)
CM3296 Molecular Modelling : Theory and Practice
EE3331C Feedback Control Systems
EE4212 Computer Vision
EE4305 Fuzzy/Neural Systems for Intelligent Robotics
EE4307 Control Systems Design and Simulation
EE4308 Autonomous Robot Systems
EE4309 Robot Perception
EE4704 Image Processing and Analysis
EE4705 Human Robot Interaction
ESP3201 Machine Learning in Robotics and Engineering
ESP5402 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
ME4291 Finite Element Analysis

This new specialisation aims to better align our program 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. The Engineering Science topic is naturally in many of the state-of-the-art instruments in the healthcare industry e.g. x-rays in computerized tomography (CT), gamma rays/radionuclides in nuclear medicine, magnetic fields and radio frequencies in magnetic resonance imaging (MRI), ultrasound in ultrasound imaging and Doppler measurements, focused ion beams for cancer therapy.

Elective Courses (Choose any FIVE)
BN3202 MusculoSkeletal Biomechanics
BN3402 Bio-Analytical Methods in Bioengineering
BN4202 Biofluids Dynamics
EE3331C Feedback Control Systems
EE4704 Image Processing and Analytics
EE4705 Human Robot Interaction
ESP3201 Machine Learning in Robotics and Engineering
PC3232 Nuclear and Particle Physics
PC3243 Photonics
PC3247 Modern Optics
PC3267 Biophysics
PC3294 Radiation Lab
PC3295 Radiation for Imaging and Therapy in medicine