Research Fellow (Advanced Research and Technology Innovation Centre Fellowship Programme)

NATIONAL UNIVERSITY OF SINGAPORE; Singapore; On-site; SGD 60,000 - 90,000; Full time

Job summary

The Advanced Research and Technology Innovation Centre (ARTIC) Fellowship Programme at the National University of Singapore invites outstanding researchers to pursue independent work for 18 to 24 months under the mentorship of designated Professors. The Research Fellow will be based in the department of the appointed Professor.

Applicants should have recently earned a PhD and a strong publication record, with excellent written and verbal communication skills.

Qualifications

• PhD must be obtained within the last 6 years.
• Strong publication record is required.
• Excellent written and verbal communication skills.

Responsibilities

• Conduct independent research under the mentorship of designated Professors.
• Publish findings and contribute to ongoing projects within the host department.

Skills

Communication skills

Research publication track record

Education

PhD in a relevant field

Job description

Job Description

The Advanced Research and Technology Innovation Centre (ARTIC) Fellowship Programme (18 to 24 months) open to outstanding researchers, provides early career researchers with the opportunity to conduct independent research under the mentorship of designated Professors. The Research Fellow position will be based under the department of the Professor, not under the Dean's Office.

Fields of Research

• Information and Communication Technology (ICT)
• Electrical and Electronics Engineering
• Computer and Data Science and Engineering, particularly interested in:
  • Long-Term Memory for Agents Across Devices
  • Cross-Layer Co-Design of Processor Architectures and Systems Software for Large Models
  • Algorithm-Memory-Execution Co-Design for Ultra-Large Sparse Models
  • Software-Defined Next-Generation NoC: Converging Communication, Computation, and Coordination
  • Computing for Embodied Intelligence: Device-Edge-Cloud Collaboration for Closed-Loop Physical AI
  • Toward Self-Optimizing Large-Model Training: Perception-Driven Compute-Communication Co-Orchestration
  • Enabling Future PIM: Collaborative Physical Design for Multi-Tier 3D DRAM-PIM
• Other related fields as specified above.

Qualifications

• Obtained PhD degree within 6 years prior to the commencement of this research role.
• Strong research publication record is required.
• Excellent communication skills, both written and verbal.