AI Offense-Defense Dynamics Lead Researcher

M.Sc. or higher in Computer Science, Cybersecurity, Criminology, Security Studies, AI Policy, Risk Management, or a related field. Demonstrated experience with complex systems modeling, risk assessment methodologies, or security analysis. Strong understanding of dual-use technologies and factors influencing offense-defense applications. Deep understanding of modern AI systems (LLMs, multimodal models, autonomous agents) and their technical architectures. Experience in Security mindset, Security studies research, Cybersecurity, Safety engineering, AI governance, Operational risk management, Systems dynamics modeling, Network theory, Complexity science, Adversarial analysis, or Technical standards development. Ability to develop qualitative frameworks and quantitative models capturing sociotechnical interactions. Record of relevant publications or research contributions related to technology risk, governance, or security. Exceptional analytical thinking with ability to identify non-obvious path dependencies and feedback loops in complex systems.

Develop quantitative system dynamics models capturing interrelationships between technological, social, and institutional factors influencing AI risk landscapes. Design analytical models and simulations to identify leverage points for policy interventions. Expand and operationalize offense/defense dynamics taxonomy, developing metrics and models. Build empirically-informed analytical frameworks using documented cases of AI misuse and beneficial uses. Research how technical characteristics interact with sociotechnical contexts to determine offense-defense balances. Build public understanding of offense-defense dynamics through various communication channels. Create tools and methodologies to assess new AI models for offense-defense implications. Draft evidence-based guidance for AI governance. Translate research findings into actionable guidance for stakeholders.