Job DescriptionThe Cybersecurity Group at United Arab Emirates University invites applications for a Postdoctoral Fellow position in an innovative research project focused on AI-enabled binary analysis and cyber threat intelligence. This is an exceptional opportunity to work at the forefront of cybersecurity research, combining deep learning methodologies with classical program analysis techniques to address critical challenges in malware detection and IoT security. This cutting-edge research initiative aims to develop a robust platform that leverages both deep learning and traditional program analysis techniques for machine code (binary) analysis. The project will establish experimental benchmarks to compare existing techniques and deliver a comprehensive binary analysis infrastructure that integrates state-of-the-art AI capabilities with proven classical methods. The research directly supports the broader AI-Enabled Search Engine for Cyber Threat Intelligence initiative, which processes approximately 3.0 TB of daily passive measurements to identify and characterize Internet-scale compromised IoT devices and botnets. This work is critical to strengthening the UAE’s cybersecurity posture and advancing the global understanding of IoT security threats. Project Lead: Dr. Saed AlrabaeeMinimum QualificationEducational Background • PhD completed in Information Security, Information Systems, Computer Science, Computer Engineering, or closely related field • Strong academic record from a rigorous graduate program with demonstrated research excellence Technical Expertise • Deep Learning: Expertise in neural network architectures, training methodologies, and their application to security problems (strongly preferred) • Binary Analysis: Proficiency in reverse engineering, program analysis, and malware examination (strongly preferred) • Reverse Engineering Tools: Working knowledge of at least one major framework including IDA Pro, OllyDbg, Ghidra, Binary Ninja, or similar platforms • Programming Skills: Strong coding abilities in Python, C/C++, or other relevant languages • IoT and android expertise • System Building: Experience in developing research prototypes, security tools, or experimental infrastructure (highly favorable) • Applied Cryptography: Background in cryptographic implementations or security protocol analysis (favorable) Research Capabilities • Required: Strong research aptitude relevant to binary analysis and deep learning security applications (to be assessed through interviews) • Required: Demonstrated ability to write high-quality research papers and academic articles • Significant Advantage: Published research articles in top-tier security conferences (IEEE S&P, USENIX Security, CCS, NDSS) or journals • Significant Advantage: Publicly available research artifacts including tools, codebases, plugins, or datasets demonstrating technical capability in binary analysis or deep learning securityPreferred Qualification
