Research Fellow (Energy-aware Accelerated Computing)

Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal.

NUS Career Portal link https://careers.nus.edu.sg/job/Research-Fellow-%28Energy-aware-Accelerated-Computing%29/33948-en_GB/

We regret that only shortlisted candidates will be notified.

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.