NUS – Institute of Data Science

Job Opportunities – AI for Cybersecurity – Automatic Agentic Penetration Testing (Posted on: 6 Oct 2025)

Overview

We are looking to recruit Research Fellows and Research Assistants 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.

Research Fellow: (1 year contract)

Job Summary

The Research Fellow will be responsible for undertaking in-depth research and innovation in machine learning, data science, and artificial intelligence on cybersecurity that leads to publications in top-tier international conferences and journals, as well as real-world implementations. The role includes designing novel algorithms, building robust software systems, and collaborating with stakeholders to translate research into practical tools and workflows. Candidates will be working alongside researchers and practitioners in AI, cybersecurity, and software engineering.

Interested candidates can submit their applications here. 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.

Responsibilities:

Develop new concepts and algorithms in data science, machine learning, and artificial intelligence for cybersecurity and automated penetration testing;
Ability to work in a fast-paced research environment;
Be up to date on state-of-the-art methodologies in related technical fields and application domains;
Develop ideas for application of research outcomes;
Contribute to knowledge exchange activities with external partners and collaborators.

Requirements:

PhD in Computer Science, with specialization related to cybersecurity, machine learning, data mining or artificial intelligence;
Proven ability to conduct independent research with a strong and relevant publication record;
Prior AI expertise with a strong publication track record in areas such as machine learning, deep learning, reinforcement learning or LLMs/agents;
Knowledge and demonstrable interest in cybersecurity applications (e.g., penetration testing, vulnerability discovery);
Proficiency in programming and software engineering (Python preferred), including experience with ML frameworks (e.g., PyTorch, TensorFlow);
Excellent interpersonal communication and oral presentation skills in English.

Research Assistant: (1 year contract)

Job Summary

The Research Assistant 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.

Job Summary

The Research Assistant will be responsible for data extraction, data standardization and integration, implementations for algorithms and methodologies based on state-of-the-art research in machine learning and big data for collaborative machine learning.

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

Requirements:

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.