AY2021 & AY2022 & AY2023 & AY2024 Cohort
Nanoscience and Technology (NANO)
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 (Choose any FIVE) |
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Molecular Modelling : Theory and Practice Note:Â prerequisite is PC2130B. To submit an appeal during CourseReg |
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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 |
Surface Physics |
Energy Science and Technology (EST)
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) | |
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 |
Optimization of Energy System | |
ESP5402 /Â ESP4403 | Transport Phenomena in Energy Systems (offered every alternate AY starting from AY2025/2026) |
ME3122 | Heat Transfer |
ME3221 |
Sustainable Energy Conversion Note: No longer offered from AY2025/2026 |
ME4223 | Thermal Environmental Engineering |
ME4225 |
Applied Heat Transfer Note: 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)
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 specialisation also gives the opportunity to discover assorted computational aspects associated with robotics and artificial intelligence.
                Elective Courses (Choose any FIVE) | |
Molecular Modelling : Theory and Practice Note: prerequisite is PC2130B. To submit an appeal during CourseReg |
|
EE3331C | Feedback Control Systems |
EE4212 | Computer Vision |
EE4305 |
Fuzzy/Neural Systems for Intelligent Robotics Note: no longer offered from AY2024/2025 |
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 new specialisation aims to better align our 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. 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 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 |
Biophysics | |
Radiation Labatory | |
Radiation for Imaging and Therapy in medicine |