Ontario Tech University in Canada is seeking a Post-Doctoral Fellow in Cybersecurity to conduct advanced research at the intersection of large language models (LLMs) and malware. The position focuses on exploring how modern foundation models can learn transformation rules to bypass static and signature-based detection, contributing to both offensive and defensive aspects of AI in cybersecurity.

The successful candidate will lead research involving dataset preparation, domain-specific fine-tuning of LLMs for code mutation, and the development of automated validation pipelines against commercial antivirus and endpoint detection and response (AV/EDR) engines. Additional responsibilities include model compression and quantization for deployment in endpoint security scenarios.

Applicants must have a PhD in Computer Science with a specialization in machine learning or cybersecurity. Required skills include proficiency with PyTorch, Hugging Face (Transformers, Datasets), and experience with malware sandboxing. The position is ideal for researchers interested in the evolving landscape of AI-driven cybersecurity and the offensive-defensive balance in this domain.

For more information and to apply, candidates should visit the Ontario Tech University careers portal. The position offers an opportunity to work in a cutting-edge research environment focused on AI, cybersecurity, and practical deployment of machine learning models for malware detection and prevention.