Research Fellow in AI/ML for Semiconductor Failure Analysis at NUS
Job Description
NUS’s Department of Electrical and Computer Engineering is hiring a Research Fellow in applied AI for semiconductor failure analysis and fault isolation. The fellow develops machine-learning-guided diagnostics for hybrid electronics, integrates them into failure-analysis workflows and works closely with industry partners.
At a glance
- Post: Research Fellow (AI/ML Failure Analysis)
- Department: Electrical and Computer Engineering
- Posted: 14 April 2026
- Apply: open until filled (re-checked 14 October 2026)
What the post involves
- Research AI/ML methods for semiconductor failure analysis
- Develop algorithms for defect detection, classification and failure analysis
- Lead integration of ML-driven diagnostic tools with instruments and test platforms
- Analyse large experimental and simulation datasets and benchmark AI predictions
- Mentor junior researchers, deliver milestones and act as a liaison with industry partners
Why this post matters
Finding why a chip failed is slow, expert work, and AI tools that point to likely defects can save weeks. Industry partners are involved, so this post combines research with problems chip makers actually face. It is a good bridge for AI researchers who want to move into the semiconductor industry.
What NUS is looking for
- A Ph.D. in electrical engineering, computer science or a related field
- Machine learning experience applied to physical or engineering data
- Software skills for tools that connect to instruments
Nice to have
- Semiconductor failure analysis or test experience
Pay and location
NUS does not state a salary in this advertisement; research staff pay in Singapore follows the institution’s own scales and depends on qualifications and experience.
How to apply
Apply through the official NUS job posting. NUS’s posting does not give a closing date, so the role is open until filled; ResearchJobs.in will re-check this listing on 14 October 2026. Check the posting for location and work-authorisation details before you apply.
See all our research fellow jobs, or browse more research jobs on ResearchJobs.in.
Hiring institution: National University of Singapore
Official advertisement: careers.nus.edu.sg
How to prepare for this application
- ML on real data: show defect or anomaly detection work.
- Instruments: software that talked to lab equipment helps.
- Industry: experience with company partners is a plus.
- Mentoring: the post includes supervising juniors.
About the National University of Singapore
NUS is Singapore's oldest and largest university and one of Asia's leading research universities. Its College of Design and Engineering hosts the departments behind these posts, with cleanrooms and labs on the Kent Ridge campus.
