Job Type:
Term (Fixed Term)
Overview
RAND’s Center on AI, Security, and Technology (CAST) , part of the Global and Emerging Risks (GER) Division, is seeking researchers to advance the technical foundations of AI safety. This role is intended for researchers with deep expertise in areas such as theoretical computer science, cryptography, formal methods, programming languages, systems security, computer architecture, distributed systems, or machine learning systems.
You will conduct original research on technically challenging problems at the intersection of AI and security. Researchers are expected to exercise independent scientific judgment in identifying important questions, developing appropriate methods, and leading projects from problem formulation through analysis, implementation, experimentation, and publication. The work may span fundamental research, systems building, empirical evaluation, and technical analysis.
Your research will inform both the broader technical community and analysis delivered to senior government and industry leaders. You will communicate results through peer-reviewed publications, technical reports, research artifacts, and policy-facing products for both technical and non-technical audiences. One example of RAND's work in this area is the Securing AI Model Weights report.
This position is structured as a three-year appointment with options to renew and explore opportunities for longer-term employment at RAND thereafter.
Qualifications
All research positions at RAND require excellent analytic skills; the ability to communicate clearly and effectively, both orally and in writing; the ability to work effectively as a member of a multi-disciplinary team; and a strong commitment to RAND's core values of quality and objectivity.
Required:
Demonstrated ability to conduct independent, original technical research.
Deep expertise in at least one area such as theoretical computer science, cryptography, formal methods, programming languages, computer security, systems, computer architecture, or machine learning systems.
Ability to identify and formulate important research problems, showing creativity and initiative in the conception and execution of projects.
Strong programming or systems-building ability in languages such as Python, Rust, Go, C/C++, or equivalent tools appropriate to the candidate's research area.
Demonstrated ability to lead complex research projects from conception through completion.
Excellent written and verbal communication skills for both technical and non-technical audiences.
Ability to work effectively in a collaborative, geographically distributed environment.
Candidates should demonstrate a strong research record through peer-reviewed publications, significant research artifacts, or equivalent technical contributions. Strong candidates will often have published at leading venues such as NeurIPS, ICML, ICLR, COLT, USENIX Security, IEEE Symposium on Security and Privacy, ACM CCS, NDSS, STOC, FOCS, SODA, CRYPTO, TCC, SOSP, OSDI, CAV, POPL, PLDI, OOPSLA, ICFP, or comparable venues.
Preferred:
PhD in Computer Science, Electrical Engineering, Mathematics, Physics, or a closely related technical field. Late stage PhD candidates with an anticipated dissertation defense date will also be considered.
Expertise spanning multiple areas of computer science.
Experience with formal methods, verification, or cryptography.
Experience in systems security, hardware security, confidential computing, or secure systems design.
Experience with machine learning systems, distributed training, inference infrastructure, accelerators, or large-scale computing systems.
Experience developing research prototypes or experimental systems.
Experience with security analysis, vulnerability research, adversarial evaluation, or red teaming.
Experience translating technical research for policymakers, research funders, or senior technical decision-makers.
Prior experience specifically in AI security is not required. We…