Research Fellow (Energy-aware Accelerated Computing)

Q: What qualifications are required for this Research Fellow position?

Candidates must hold a PhD in Electrical Engineering, Materials Science, Applied Physics, or a closely related field . Prior hands-on experience with cleanroom fabrication and optical/electrical characterization is advantageous. A strong publication record in peer-reviewed journals and the ability to work both independently and collaboratively are essential. Learn how to craft a standout academic profile with our guide on writing a winning academic CV .

Q: What research areas will the successful candidate explore?

The Research Fellow will contribute to energy-aware accelerated computing through the design of neuromorphic architectures and memristor-based circuits . Key areas include AI accelerator hardware , in-memory computing , algorithm-hardware co-design , and machine learning integration . This role offers the chance to publish in top-tier venues and collaborate across disciplines. Explore other postdoctoral research opportunities at leading institutions.

Q: Where is the position located and what is the work environment?

The job is based at the Kent Ridge Campus of the National University of Singapore (NUS) , a world-class hub for engineering and technology research. The fellow will join an interdisciplinary team with access to state-of-the-art cleanroom and characterization facilities. Browse all current higher education jobs at NUS and beyond.

Q: Is this a fixed-term appointment? What should I know?

Yes, the position is offered as a fixed-term contract . Research fellowships of this nature typically run for one to three years, providing an excellent opportunity to build a publication record and secure future permanent roles. For strategies on thriving in such positions, read our advice on postdoctoral success .

Q: How can I apply and improve my chances of selection?

Prepare a detailed academic CV highlighting your cleanroom and characterization skills , a compelling cover letter outlining your research vision , and ensure your publication list is up-to-date. Tailor your application to the specific requirements of neuromorphic and accelerator hardware design . For further guidance, check out our resource on how to write a winning academic CV and learn about what employers seek .

Job Description

We are seeking a highly motivated and skilled Research Fellow to join our team on a project to demonstrate high-performance AI accelerator hardware. 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.

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.

Open to fixed term contract.

Frequently Asked Questions

🎓What qualifications are required for this Research Fellow position?

Candidates must hold a PhD in Electrical Engineering, Materials Science, Applied Physics, or a closely related field. Prior hands-on experience with cleanroom fabrication and optical/electrical characterization is advantageous. A strong publication record in peer-reviewed journals and the ability to work both independently and collaboratively are essential. Learn how to craft a standout academic profile with our guide on writing a winning academic CV.

🔬What research areas will the successful candidate explore?

The Research Fellow will contribute to energy-aware accelerated computing through the design of neuromorphic architectures and memristor-based circuits. Key areas include AI accelerator hardware, in-memory computing, algorithm-hardware co-design, and machine learning integration. This role offers the chance to publish in top-tier venues and collaborate across disciplines. Explore other postdoctoral research opportunities at leading institutions.

📍Where is the position located and what is the work environment?

The job is based at the Kent Ridge Campus of the National University of Singapore (NUS), a world-class hub for engineering and technology research. The fellow will join an interdisciplinary team with access to state-of-the-art cleanroom and characterization facilities. Browse all current higher education jobs at NUS and beyond.

⏳Is this a fixed-term appointment? What should I know?

Yes, the position is offered as a fixed-term contract. Research fellowships of this nature typically run for one to three years, providing an excellent opportunity to build a publication record and secure future permanent roles. For strategies on thriving in such positions, read our advice on postdoctoral success.

📝How can I apply and improve my chances of selection?

Prepare a detailed academic CV highlighting your cleanroom and characterization skills, a compelling cover letter outlining your research vision, and ensure your publication list is up-to-date. Tailor your application to the specific requirements of neuromorphic and accelerator hardware design. For further guidance, check out our resource on how to write a winning academic CV and learn about what employers seek.