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Your application will be processed only if you apply via NUS Career Portal

We regret that only shortlisted candidates will be notified.

Overview

We are looking to recruit a Research Assistant/ Associate for the project "AI for Cybersecurity - Automatic Agentic Penetration Testing", which will be hosted at the Institute of Data Science (IDS), National University of Singapore (NUS) and led by Prof Ng See Kiong. This project advances state-of-the-art AI methods to create effective AI agents for automated penetration testing. Selected candidates will contribute to deep AI research as well as focused translational work and system development for real-world users and industry partners.

Only shortlisted candidates will be notified. Please include links to your GitHub repositories showcasing your best project relevant to these topics in your CV/cover letters.

Job Description

Job Summary: The Research Assistant/ Associate will support research and engineering activities in AI for automated, responsible penetration testing. You will help design, implement, and evaluate agentic AI approaches; build and maintain software prototypes and experimental testbeds; and assist with data, documentation, and stakeholder engagement. This role provides hands-on experience across AI research, cybersecurity tooling, and practical deployment at IDS.

Responsibilities:

• Design and write robust, readable, and reusable code components and applications to implement state-of-the-art research outcomes in cybersecurity, machine learning, artificial intelligence, and big data.
• Perform data engineering tasks including data cleansing and processing for analysis of real-world datasets.
• Assists with the editing and preparation of manuscripts, reports and presentations.
• Participate in presentations and demos for exhibiting work at appropriate events.

Qualifications

• Bachelors or Masters in Computer Science with a focus in Cybersecurity, AI, Machine Learning and Big Data.
• Solid programming and application development skills (Python preferred) and experience with ML frameworks (e.g., PyTorch, TensorFlow) and modern development practices (Git, testing, CI/CD).
• Ability to develop robust systems and prototypes with fast turn-around.
• Possesses research background with ability to read and understand methodologies in research papers.
• Fluent in English and good team-player.
• Prior AI expertise with knowledge and interest in cybersecurity applications (e.g., penetration testing, vulnerability discovery, secure software engineering) and LLM-based agents is preferred.