Research Assistant, School of 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-Assistant%2C-School-of-Computing/32843-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

The National University of Singapore invites applications for the position of Research Assistant in the Department of Computer Science, School of Computing (SoC), to work on a CRPO-funded research project titled A Closed-Loop, Interpretable, and Lightweight AI-based IAM Framework. The project is a collaboration between NUS and i-Sprint Innovations Pte Ltd, and aims to advance a self-improving, explainable, and edge-ready AI-driven security framework for Identity and Access Management (IAM). SoC is strongly committed to research excellence in all its dimensions and seeks to play an active role both internationally and locally in the core and emerging areas of Computer Science and Information Systems.

The Research Assistant will work closely with the Principal Investigator and the project team on research and development of an LLM-driven analyst-copilot system for cybersecurity. Specific responsibilities include: (i) curating and structuring domain-specific knowledge corpora (IAM manuals, compliance documentation, threat-intelligence reports, anomaly-detection outputs) into RAG-ready stores (ii) fine-tuning and benchmarking large language models for retrieval-augmented generation in the cybersecurity domain (iii) designing and building the analyst-facing copilot interface and natural-language query layer integrating with the industry collaborator's (i-Sprint Innovations) product surfaces (iv) contributing to edge-LLM distillation for offline / cloud-independent deployment (v) preparing technical documentation, experiments, and contributions toward research publications and patent disclosures. The candidate should possess experience or strong interest in at least one of the following research areas:

• Large Language Models (LLM training, fine-tuning, prompt engineering)
• Retrieval-Augmented Generation (RAG), agentic systems, and copilot design
• Cybersecurity, Digital Forensics, and Identity & Access Management (IAM)
• Document AI, OCR pipelines, and knowledge-corpus construction
• Software Engineering for AI/ML systems (Python, PyTorch/TensorFlow)

Only shortlisted candidates will be notified.

Job Requirements

• A Bachelor's degree with Honours (or equivalent qualification) in Computer Science, Cybersecurity, Information Systems, Software Engineering, or a closely related discipline and
• Demonstrated experience in research and/or industry projects involving applied AI/ML, large language models, document AI, cybersecurity, or software engineering. Strong programming skills in Python (and/or Java) and proficiency in English are essential. Prior exposure to LLM fine-tuning, RAG systems, agentic frameworks, or analyst-facing tooling will be considered an advantage.