Research Fellow, Mechanical Engineering
This is A*STAR Industrial Alignment Funding (IAF) sponsored project to conduct industry related R&D projects collaborated between NUS and SIMTech (Singapore Institute of Manufacturing Technology) A*STAR in the areas of machine learning for anomaly pattern detection on product quality control and advanced optimization for Industry 4.0 manufacturing execution system through Cyber Physical Production System (CPPS). The successful candidate will participate in the team with researchers from NUS and SIMTech to develop the solution for anomaly pattern detection on product quality control and a prototype system to demo the solution to industrial partners. The successful candidate will be exposed to technologies such as big data analytics, data mining, machine learning, artificial intelligence, advanced optimization, etc.
- PhD in Computer Engineering, Computer Science, Electrical and Electronic Engineering, Mechanical Engineering, or related disciplines.
- Research experience in machine learning, data mining, big data analytics, artificial intelligence, advanced optimization, machine connectivity, embedded system, etc.
- Good working knowledge in Java, C/C++, C#, database, MatLab, Python Programming.
- Creative, self-motivated, and excellent communication skills.
- Entry level graduates are welcomed For interest candidate, please send your CV to the contact person. Professor Lu Wen Feng Email address: firstname.lastname@example.org Only shortlisted candidates will be notified through email for interview.
Location: Kent Ridge Campus
Department : Mechanical Engineering