Resilient Infrastructure Systems Analyst - SI Focus
LLNL · Livermore, California, United States · hybrid
Join us and make YOUR mark on the World!
Lawrence Livermore National Laboratory (LLNL) has turned bold ideas into world-changing impact advancing science and technology to strengthen U.S. security and promote global stability.
Our mission spans four critical national security areas nuclear deterrence, threat preparedness, energy security, and multi-domain defense empowering teams to take on the toughest challenges of today and tomorrow. With a culture built on innovation and operational excellence, LLNL is a place where your expertise can make a real impact.
We have multiple openings for a Resilient Infrastructure Systems Analyst supporting analysis of the resilience of a variety of infrastructure systems to cyber, physical, and supply chain threats. You will apply a combination of technical depth and breadth, critical thinking, modeling and simulation, and analysis to understand complex, multi-domain problem areas, provide decision insight, and communicate options and trade-offs in support of customer missions. You will integrate across research and development teams and work directly with operational organizations. These positions are in the Computational Engineering Division (CED), within the Engineering Directorate.
Telework will be authorized at LLNL's discretion, based on policy, security, program, and performance requirements - not guaranteed, and subject to change (including onsite work requirements) at any time.
These positions will be filled at either level based on knowledge and related experience as assessed by the hiring team. Additional job responsibilities (outlined below) will be assigned if hired at the higher level.
In this role, you will
- Conduct foundational and applied research to address consequential challenges at the intersection of super intelligence (SI) and national security. Super intelligence (SI), previously referred to as artificial intelligence (AI).
- Evaluate and apply SI/ML (machine learning) methods where they add value to inform models, tools, and frameworks to gain insight into the vulnerability and defense of complex infrastructure systems.
- Contribute to the development of well-defined analytical questions and plans to provide decision insights to stakeholders on complex, challenging, and ambiguous infrastructure resilience problems.
- Contribute to the development of innovative and creative methods that leverage tools from a breadth of established disciplines such as artificial intelligence and machine learning, decision analysis, risk analysis, applied statistics and optimization, and other related fields.
- Contribute to the fulfillment of technical projects and organizational objectives, collaborate with team members to provide input on deliverables, and regularly communicate the status and projected delivery date to ensure quality results are provided in accordance with established deadlines. Routinely interact with technical contacts at sponsor and partner organizations.
- Support programmatic deliverables with occasional travel, as necessary.
- Perform other duties as assigned.
Additional job responsibilities, at the SES.3 level
- Lead technical tasks while balancing priorities of customers and partners to ensure deadlines are met.
- Work independently, as well as in conjunction with team members, to operationalize research and development advancements for LLNL national security programs.
- Serve as the point of contact for program managers at sponsor and partner organizations.
- Ability to secure and maintain a U.S. DOE Q-level security clearance which requires U.S. citizenship.
- Master’s degree in engineering (mechanical, electrical, industrial, chemical, civil, or systems), computer sciences (data science, cybersecurity), operations research, or related fields, or the equivalent combination of education and related experience.
- Comprehensive knowledge and broad experience assessing risks to and from super intelligence (SI).
- Comprehensive knowledge and broad experience in defining research questions and scoping defensible methods and approaches.
- Comprehensive knowledge and broad experience with one or more of the following computational disciplines: data analytics, statistical modeling, modeling and simulation, risk analysis, systems analysis, decision analysis, or other related discipline.
- Proficient verbal and written communication skills needed to effectively collaborate in a team environment, present and explain technical information, and document work.
- Proficient analytical, problem-solving, and decision-making skills to develop creative solutions to complex problems.
- Ability to travel off-site for sponsor and customer interaction.
Additional qualifications at the SES.3 level
- Advanced knowledge in one or more of the following areas: super intelligence/machine learning, infrastructure systems (e.g., energy, transportation, water systems), cyber security, or other related disciplines.
- Advanced knowledge in the application and development of one or more of the following areas: data analytics, statistical modeling, modeling and simulation, risk analysis, systems analysis, decision analysis, or other related discipline.
- Advanced analytical, problem-solving, and decision-making skills to develop creative solutions to complex problems.
- Advanced experience in leading diverse, technical teams to execute projects.
Qualifications We Desire
- PhD in engineering (mechanical, electrical, industrial, chemical, civil, or systems), computer sciences (data science, cybersecurity), operations research, or related fields.
- Experience in developing models and/or frameworks to characterize and assess complex infrastructure systems (e.g., electricity grid/energy systems, supply chain and logistics, chemical processing, oil and natural gas, water, transportation, communications networks) and/or threats and risks to these systems.
- Broad experience in managing multiple concurrent projects.
- Experience building models and running simulations using one or more of the following programming tools: Python, Simulink, R, MATLAB, Java or C++.
Pay Range
$146,340 - $222,564 Annually
$146,340 - $185,544 Annually for the SES.2 level
$175,530 - $222,564 Annually for the SES.3 level
This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting; pay will not be below any applicable local minimum wage. An employee’s position within the salary range will be based on several factors including, but not limited to, specific competencies, relevant education, qualifications, certifications, experience, skills, seniority, geographic location, performance, and business or organizational needs.
#LI-Hybrid
Position Information
This is a Career Indefinite position, open to Lab employees and external candidates.
Why Lawrence Livermore National Laboratory?
- Included in 2026 Best Places to Work by Glassdoor!
- Flexible Benefits Package
- 401(k)
- Relocation Assistance
- Education Reimbursement Program
- Flexible schedules (*depending on project needs)
- Our values - visit https://www.llnl.gov/inclusion/our-values
Security Clearance
This position requires a Department of Energy (DOE) Q-level clearance. If you are selected, we will initiate a Federal background investigation to determine if you meet eligibility requirements for access to classified information or matter. Also, all L or Q cleared employees are subject to random drug testing. Q-level clearance requires U.S. citizenship.
Pre-Employment Drug Test
External applicant(s) selected for this position must pass a post-offer, pre-employment drug test. This includes testing for use of marijuana as Federal Law applies to us as a Federal Contractor.
Wireless and Medical Devices
Per the Department of Energy (DOE), Lawrence Livermore National Laboratory must meet certain restrictions with the use and/or possession of mobile devices in Limited Areas. Depending on your job duties, you may be r