Research Fellow (Computer Science/Cybersecurity/Artificial Intelligence)

Young and research-intensive, Nanyang Technological University, Singapore (NTU Singapore) is ranked among the world’s top universities. NTU’s College of Computing and Data Science (CCDS) is a leading college that is known for its excellent curriculum, outstanding and impactful research, and world-renowned faculty.

A hot bed of cutting-edge technology and groundbreaking research, the College aims to groom the next generation of leaders, thinkers, and innovators to thrive in the digital age. Located in the heart of Asia, NTU’s College of Computing and Data Science is an ‘exciting place to learn and grow. We welcome you to join our community of faculty, students and alumni who are shaping the future of AI, Data Science and Computing.

We are seeking for a highly motivated Research Fellow to drive cutting-edge research and development in AI-driven cybersecurity, focusing on intelligent and explainable automation for Security Operations Centers (SOCs).

Key Responsibilities:

• Design and develop AI-driven, knowledge-based agentic systems for automated alert triage and investigation in SOC environments, contributing to the AutoSOC platform

• Build explainable AI models that integrate planning, memory, and learning capabilities

• Develop and optimize data-driven algorithms for anomaly detection and incident response

• Implement scalable, modular, and containerized solutions compatible with platforms such as Wazuh and MXOC

• Apply advanced machine learning techniques (e.g., reinforcement learning, generative AI, and interpretable AI) to enhance system adaptability and performance

• Collaborate with industry partners for system integration and validation

• Contribute to prototype development for commercialization

• Produce high-quality research outputs, including publications and technical reports

Job Requirements:

• PhD in Computer Science, Cybersecurity, Artificial Intelligence or related fields

• Strong background in AI/ML, particularly in interpretable AI, generative models, reinforcement learning or agent-based systems

• Experience in large-scale data processing, signal analysis or real-world system deployment

• Proficiency in programming (e.g., Python) and ML frameworks (e.g., PyTorch, TensorFlow)

• Experience with edge deployment, system integration, or containerization is an advantage

• Strong publication record in reputable journals/conferences, with ability to conduct independent research

• Good communication skills and ability to work in a team with both academic and industry stakeholders

• Demonstrated ability in developing AI models for complex applications (e.g., healthcare AI, wearable systems, or intelligent platforms)

We regret that only shortlisted candidates will be notified.