Research Associate/ Fellow (AI for Cybersecurity - Automatic Agentic Penetration Testing)

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Job Description:

Overview

We are looking to recruit a Research Fellow for the project AI for Cybersecurity - Automatic Agentic Penetration Testing, which will be hosted at the , 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 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.

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 face-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.