Total 3 security job vacancies in Education / Training category

We are seeking to appoint a Research Associate who will contribute to NTU's mission of advancing system security, privacy-preserving computing, and intelligent vulnerability analysis. The ideal candidate will provide strategic research support in bridging low-level system architecture with AI-driven security solutions. This role requires strong expertise in developing formally verified confidential computing environments, optimizing machine learning architectures for secure inference, and building multi-agent pipelines for protocol specification analysis. By driving these interdisciplinary efforts, the appointed researcher will play a pivotal role in NTU's strategic initiatives to build trustworthy, resilient, and efficient computing ecosystems, while fostering innovative collaborations across academia and industry.

Key Responsibilities:

• Conduct cutting-edge research at the intersection of system security, privacy-preserving computing, and intelligent vulnerability analysis.

• Design and implement formally verified, hardware-assisted isolation environments for confidential cloud computing.

• Formulate optimization strategies for machine learning architectures to enable high-performance secure inference.

• Develop multi-agent frameworks driven by large language models to systematically analyze protocol specifications and predict implementation vulnerabilities.

• Collaborate with academic and industry partners to translate advanced security paradigms into real-world applications.

• Prepare and co-author high-quality research papers for premier venues in security, systems, and software engineering.

• Contribute to proposal writing and grant applications in hardware-software co-design and AI-driven security.

• Support the supervision and mentorship of undergraduate and postgraduate students in related projects.

• Assist in building experimental platforms and validation datasets for protocol analysis and confidential computing frameworks.

Requirements:

• Masters degree in Computer Science, Cyber Security, or a related discipline.

• Research or applied experience in system security.

• Experience with privacy-preserving machine learning, AI-driven vulnerability analysis, and vulnerability detection tools.

• Knowledge of cryptographic protocols such as Multi-Party Computation.

• Proficiency in programming languages such as Python, C/C++, and Java.

• Strong academic writing and publication track record, with contributions to international conferences (e.g., ICSE).

• Strong analytical and problem-solving skills, particularly in bridging low-level system architectures.

• Proficiency in experimental design, evaluation benchmarks, and reproducibility of results.

• Excellent communication and collaboration skills in multidisciplinary teams.

• Ability to mentor and support students in research activities and software projects.

We regret that only shortlisted candidates will be notified.

Interested applicants are invited to apply directly at theNUS Career Portal. Please note your application will only be processed if youapply via NUS Career Portal.

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Fellow%2C-Security-%28School-of-Computing%29/33419-en_GB/?st=4BE945D60CCC38A4FBFF14E6E239368304BA2DD3

We regret that only shortlisted candidates will be notified.

Job Description

The National University of Singapore invites applications for the position of Research Fellow in the Department of Computer Science, School of Computing (SoC). SoC is strongly committed to research excellence in all its dimensions: Searching for fundamental results and insights in developing novel computational solutions to a wide range of applications, building largescale experimental systems, developing theories and policies for effective management of information systems in organizations, and improving the well-being of society. We seek to play an active role both internationally and locally in the core and emerging areas of Computer Science and Information Systems.

The postdoctoral researcher will work on processor security and hardware testing. The role focuses on building new ways to find design bugs in processors before those processors are manufactured or deployed. This includes fuzzing, which means automatically generating many test programs to stress a processor design and expose incorrect behavior. The work will also study transient execution attacks, where a processor may briefly compute on secret data and leave traces that an attacker can observe.

The candidate will design new testing methods, build research prototypes, evaluate them on open processor designs, and publish the results in leading security and systems venues. The candidate will also help mentor PhD students, contribute to research planning, and support collaborations with academic and industry partners.

Qualifications

• The candidate should have a PhD in computer security, computer architecture, systems, or a closely related area.
• Strong experience with processor testing, hardware security, or fuzzing is expected.
• The candidate should be comfortable reading processor designs and working with simulation tools.
• Programming ability is important, especially for building research systems that can run at scale.
• The role also requires the ability to explain technical work clearly to people with different backgrounds. 
• The candidate should be able to turn a research idea into a working prototype, compare it fairly with prior methods, and write papers that make the contribution easy to understand.
• A strong record of top-tier publications is necessary.

We are seeking to appoint a Research Associate to support research in cybersecurity, trustworthy AI, and large language model security. The successful candidate will contribute to projects related to privacy-preserving AI interactions, trustworthy knowledge acquisition, and secure information processing in security-sensitive AI systems. The role will involve assisting in the design, implementation, and evaluation of methods for reducing privacy leakage, mitigating adversarial risks, and improving the security and trustworthiness of LLM-based systems. The candidate will also support the construction of research benchmarks, experimental evaluation, and the preparation of high-quality research publications. This position will contribute to NTU’s mission of advancing secure and trustworthy intelligent systems through interdisciplinary research in cybersecurity and artificial intelligence.
 

Key responsibilities:

• Conduct research on cybersecurity, trustworthy AI, and large language model security, with a focus on privacy-preserving AI interactions and secure information processing.

• Design, implement, and evaluate methods for trustworthy knowledge acquisition in LLM-based systems, including approaches to reduce privacy leakage and mitigate adversarial risks.

• Develop learning-based and evaluation-driven approaches to improve the security, reliability, and trustworthiness of AI systems in security-sensitive scenarios.

• Construct experimental platforms, benchmarks, and datasets for evaluating LLM security, privacy protection, and trustworthy AI applications.

• Conduct empirical experiments, performance analysis, and ablation studies to validate proposed methods and support reproducible research.

• Prepare and co-author high-quality research papers, technical reports, and project documentation, and collaborate with academic and industry partners on related research projects.

Requirements:

• A Master’s degree in Computer Science, Cyber Security, Artificial Intelligence, or a related discipline.

• Research or applied experience in cybersecurity, trustworthy AI, large language model security, privacy-preserving AI, or related areas.

• Experience with LLM-based systems, trustworthy knowledge acquisition, information retrieval, query rewriting, or AI security evaluation.

• Familiarity with privacy leakage, adversarial risks, secure information processing, and trustworthiness evaluation in AI or LLM-based systems.

• Experience in designing and conducting empirical experiments, including benchmark construction, dataset preparation, performance evaluation, and ablation analysis.

We regret to inform that only shortlisted candidates will be notified.