Technical skills
About this role
We are seeking to appoint a Research Fellow to contribute to NTU’s mission of advancing cutting-edge research and industry translation in software engineering and cybersecurity. The successful candidate will work on the Desay SV Transfer Project, focusing on the industrialization of automated open-source component detection and emulation-based fuzz testing technologies for automotive software systems.
The role involves developing scalable binary analysis frameworks, AI-driven program understanding techniques, and automated security testing pipelines for embedded MCU and SOC platforms. The candidate will collaborate closely with academic researchers and industry engineers to transform research prototypes into deployable, high-performance solutions aligned with industrial requirements.
Key Responsibilities
- Develop and optimize automated binary analysis and open-source component detection systems.
- Design and enhance emulation-based fuzz testing frameworks for embedded environments.
- Apply AI and large language model (LLM)-based techniques to improve program analysis and vulnerability assessment.
- Support system integration, benchmarking, deployment, and technical documentation.
- Job
Requirements
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- A PhD in Computer Science, Software Engineering, Artificial Intelligence, or a related discipline.
- Strong research track record in software engineering, AI for code, or software security (e.g., publications in reputable international venues).
- Experience in program analysis, intelligent software systems, or LLM-based code intelligence.
- Strong programming skills in Python and/or C/C++.
- Ability to work independently and collaboratively in academia–industry joint projects.
- We regret that only shortlisted candidates will be notified.
- Hiring Institution: NTU