Resilient Infrastructure Systems Analyst - SI Focus

LLNL•Livermore, CA

1d•$146,340 - $222,564•Hybrid

About The Position

Lawrence Livermore National Laboratory has multiple openings for Resilient Infrastructure Systems Analysts supporting analysis of infrastructure resilience to cyber, physical, and supply chain threats. The role applies technical expertise, critical thinking, modeling and simulation, and analysis to complex, multi-domain problem areas, providing decision insight and communicating options and trade-offs in support of customer missions. Analysts integrate with research and development teams and work directly with operational organizations. The positions are in the Computational Engineering Division within the Engineering Directorate. The analyst conducts foundational and applied research at the intersection of super intelligence (SI) and national security, evaluates SI and machine-learning methods where useful, and contributes to models, tools, and frameworks for understanding infrastructure vulnerability and defense. The role supports the development of analytical questions and plans, innovative methods drawing on disciplines such as AI/ML, decision and risk analysis, applied statistics, and optimization, and technical project deliverables. It involves collaboration with team members, regular communication with technical contacts at sponsor and partner organizations, and occasional travel. Telework may be authorized at LLNL's discretion but is not guaranteed and may change according to policy, security, program, and performance requirements. Positions are filled at either the SES.2 or SES.3 level, based on knowledge and related experience. At SES.3, responsibilities additionally include leading technical tasks, balancing customer and partner priorities, independently or collaboratively operationalizing R&D advancements for national security programs, and serving as the point of contact for sponsor and partner program managers. The position requires eligibility to obtain and maintain a DOE Q-level security clearance, which requires U.S. citizenship.

Requirements

Ability to secure and maintain a U.S. DOE Q-level security clearance; U.S. citizenship is required.
Master's degree in engineering, computer sciences, operations research, or a related field, or an equivalent combination of education and related experience.
Comprehensive knowledge and broad experience assessing risks to and from super intelligence.
Comprehensive knowledge and broad experience defining research questions and scoping defensible methods and approaches.
Comprehensive knowledge and broad experience in one or more computational disciplines, such as data analytics, statistical modeling, modeling and simulation, risk analysis, systems analysis, or decision analysis.
Proficient verbal and written communication skills for teamwork, explaining technical information, and documenting work.
Proficient analytical, problem-solving, and decision-making skills to develop solutions to complex problems.
Ability to travel off-site for sponsor and customer interaction.
At SES.3, advanced knowledge in one or more areas such as SI/ML, infrastructure systems, cybersecurity, or related disciplines.
At SES.3, advanced knowledge in applying and developing computational methods such as data analytics, statistical modeling, modeling and simulation, risk analysis, systems analysis, or decision analysis.
At SES.3, advanced analytical, problem-solving, and decision-making skills.
At SES.3, advanced experience leading diverse technical teams to execute projects.

Nice To Haves

PhD in engineering, computer sciences, operations research, or a related field.
Experience developing models or frameworks to characterize and assess complex infrastructure systems or threats and risks to those systems.
Broad experience managing multiple concurrent projects.
Experience building models and running simulations using Python, Simulink, R, MATLAB, Java, or C++.

Responsibilities

Conduct foundational and applied research on challenges at the intersection of super intelligence and national security.
Evaluate and apply SI and machine-learning methods where they add value to models, tools, and frameworks for understanding infrastructure vulnerability and defense.
Contribute to defining analytical questions and plans that provide decision insights on complex infrastructure resilience problems.
Contribute to innovative methods using disciplines such as AI/ML, decision analysis, risk analysis, applied statistics, and optimization.
Contribute to technical projects and organizational objectives, collaborate on deliverables, and communicate status and projected delivery dates to meet deadlines.
Interact with technical contacts at sponsor and partner organizations.
Support programmatic deliverables with occasional travel as necessary.
At SES.3, lead technical tasks and balance customer and partner priorities to meet deadlines.
At SES.3, operationalize research and development advancements for LLNL national security programs, independently and with team members.
At SES.3, serve as the point of contact for program managers at sponsor and partner organizations.
Perform other duties as assigned.