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Job Description
The National University of Singapore invites applications for the position of Research Assistant 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
Fuzzing is a powerful technique for finding security vulnerabilities in systems and is used by corporations regularly. In this work, we will study the role of AI in cybersecurity - by aiding fuzzing techniques with large language models.
Tasks
- Conduct Research on AI-Aided Fuzzing: Lead research efforts to explore the integration of large language models (LLMs) with fuzzing techniques for identifying security vulnerabilities in systems. Design experiments and methodologies to evaluate the effectiveness of AI-aided fuzzing in comparison to traditional methods.
- Develop AI Models for Fuzzing Enhancement: Develop and implement AI models, including deep learning architectures, reinforcement learning algorithms, and natural language processing techniques, to enhance fuzzing capabilities. Train these models on relevant datasets to improve their ability to generate meaningful inputs for fuzzing.
- Collaborate with Interdisciplinary Teams: Collaborate with interdisciplinary teams comprising cybersecurity experts, AI researchers and software engineers to integrate AI-aided fuzzing techniques into existing cybersecurity frameworks. Communicate findings and insights effectively to team members and stakeholders.
- Publish Research Findings: Document research findings in academic publications, conference papers, and technical reports. Disseminate knowledge gained from the study of AI in cybersecurity, particularly in the context of fuzzing, to the broader research community through presentations and workshops.
Qualifications
- A Bachelor's degree with Honours in a relevant area and
- Experience in research
