Formulate and investigate research questions at the intersection of cybersecurity and agentic AI behavior, including security risks, failure modes, and adversarial behavior in agentic AI systems. Design rigorous experiments, evaluations, and benchmarks for autonomous, tool-using, and multi-agent systems. Analyze results and develop research insights, methodologies, and mitigations that advance the security of AI systems. Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ years related experience (e.g., statistics, predictive analytics, research) OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field OR equivalent experience. Demonstrated research output in AI security, adversarial machine learning, agentic systems, LLM evaluation, or related areas, such as publications, preprints, technical reports, talks, open-source tools, or research artifacts Experience designing experiments, evaluations, benchmarks, or methodologies to study security-relevant behavior in AI systems, especially autonomous, tool-using, or multi-agent systems Ability to work collaboratively in an interdisciplinary team environment Ability to connect research findings to practical security guidance, mitigations, or evaluation methods for real-world AI products
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