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National University of Singapore (NUS)

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Kent Ridge Campus

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"Research Fellow (High-Performance AI Computing Systems)"

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Research Fellow (High-Performance AI Computing Systems)

Research Fellow

2026-03-24

Location

Kent Ridge Campus, Singapore

National University of Singapore

Type

Full-time Academic Research

Start Date

2026-01-20

Required Qualifications

PhD in Electrical Engineering, Materials Science, Applied Physics or related
Experience in device modeling and simulation
Hands-on cleanroom fabrication (advantage)
Strong publication record
Analytical and problem-solving skills

Research Areas

Neuromorphic Computing Architectures
AI Hardware Accelerators
Memristor Cells and Circuits
Neural Networks
Machine Learning/Deep Learning
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Research Fellow (High-Performance AI Computing Systems)

Posting Start Date: 20/01/2026

Job Description

We are seeking a highly motivated and skilled Research Fellow to join our team on a project to demonstrate high-performance AI computing systems. The successful candidate will be part of an interdisciplinary research team working on the design, fabrication, and integration of neuromorphic computing architectures targeted at next-generation AI workloads.

Key Responsibilities:

  • Conduct cutting-edge research in AI computing architectures, including neural networks hardware accelerator systems.
  • Design, model, and simulate memristor cells and circuits tailored for AI acceleration.
  • Collaborate on the fabrication and experimental characterization of integrated memristor devices and systems.
  • Develop algorithms and system-level integration strategies to harness the capabilities of AI accelerator for machine learning and deep learning tasks.
  • Publish research findings in high-impact journals and present at international conferences.
  • Mentor graduate and undergraduate students involved in the project.

Qualifications

  • PhD in Electrical Engineering, Materials Science, Applied Physics, or a related field.
  • Experience in device modeling and simulation.
  • Prior hands-on experience with cleanroom fabrication and optical/electrical characterization is an advantage.
  • Strong analytical and problem-solving skills.
  • Ability to work independently and in a collaborative team environment.
  • Excellent publication record in reputable peer-reviewed journals.

More Information

Location: Kent Ridge Campus

Organization: College of Design and Engineering

Department: Electrical and Computer Engineering

Employee Referral Eligible: No

Job requisition ID: 31506

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Frequently Asked Questions

🎓What qualifications are required for the Research Fellow position?

A PhD in Electrical Engineering, Materials Science, Applied Physics, or related field is required. Essential experience includes device modeling and simulation. Advantageous: hands-on cleanroom fabrication and optical/electrical characterization. Strong analytical skills, ability to work independently/collaboratively, and excellent publication record in peer-reviewed journals. See academic CV tips.

🔬What are the key responsibilities?

Conduct research in AI computing architectures and neural networks hardware accelerators. Design/model/simulate memristor cells/circuits for AI acceleration. Collaborate on fabrication and characterization of memristor devices. Develop algorithms/system integration for machine learning/deep learning. Publish in high-impact journals, present at conferences, mentor students. Explore research jobs.

📅What is the application deadline and start date?

Applications close on March 24, 2026 (expiration date). Posting starts January 20, 2026. Apply via requisition ID 31506. Check academic calendar for timelines.

📍Where is the position located?

Kent Ridge Campus, National University of Singapore. Department of Electrical and Computer Engineering, College of Design and Engineering. No visa sponsorship mentioned; local candidates preferred. View faculty jobs in Singapore.

👥Is there teaching or mentoring involved?

Yes, mentor graduate and undergraduate students. No explicit teaching load; focus on research, publications, conferences. Ideal for post-PhD researchers. Related: postdoc success tips.

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