Operations Research Engineer

Company Description

Join us and make YOUR mark on the World!

Are you interested in joining some of the brightest talent in the world to strengthen the United States’ security? Come join Lawrence Livermore National Laboratory (LLNL) where our employees apply their expertise to create solutions for BIG ideas that make our world a better place.

We are committed to a diverse and equitable workforce with an inclusive culture that values and celebrates the diversity of our people, talents, ideas, experiences, and perspectives. This is important for continued success of the Laboratory’s mission.

Pay Range

$132,810 - $170,556 Annually

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.

Job Description

We have an opening for an Operations Research Engineer with expertise in energy systems simulation and management, electricity markets, capacity expansion planning, stochastic optimization, and experience integrating different datasets into coherent inputs for optimization models. You will initially focus on stochastic capacity expansion models of the continental U.S. but will also support other research and analysis initiatives under investigation by the Department of Energy, Department of Homeland Security, Department of Defense, and/or other U.S. Government partners. You will work with experienced LLNL scientists and engineers and contribute to new numerical methods and analyses that provide insights to inform near and long-term strategy and technology decisions. This position is in Computational Engineering Division (CED), within the Engineering Directorate.

You will

• Support the development of optimization models for energy networks, including formulation, implementation, solution, analysis, and communication.
• Support the construction of coherent datasets to feed long-term optimal capacity expansion models of energy systems, including technology costs, geographical characteristics (solar irradiance, wind speeds, wildfire propensity, etc.), regulatory frameworks, human factors, climate and extreme weather events, among others.
• Contribute to cross-functional and multi-disciplinary teams to solve technical problems.
• Provide solutions to moderately complex problems related to modeling and simulation, or other technical analyses.
• Contribute to the development of analytical frameworks that provide insight to customers on various challenges.
• Determine methods, techniques, and evaluation criteria using independent judgment.
• Contribute information and findings from studies.
• Perform other duties as assigned.

Qualifications

• Ability to secure and maintain a U.S. DOE Q-level security clearance which requires U.S. citizenship.
• Master’s degree in physical science, engineering, operations research, economics or a related field, or equivalent combination of education and related experience.
• Demonstrated ability to process data from multiple sources into coherent datasets.
• Demonstrated competence in one or more scientific programming languages, such as Python, Julia, C++, R, Matlab, or Rust.
• Demonstrated ability to implement mathematical optimization problems using at least one algebraic modeling language, such as Pyomo (preferred), Gurobipy, JuMP, AMPL, GAMS, among others.
• Familiarity with decomposition techniques in stochastic optimization, such as Benders, ADMM, Progressive Hedging, SDDP.
• Ability to effectively manage concurrent technical tasks with competing priorities and meet deadlines that are important to project success.
• Proficient verbal and written communication skills necessary to effectively collaborate in a team environment and present and explain technical information.

Qualifications We Desire

• PhD in physical science, engineering, operations research, economics or a related field, or equivalent combination of education and related experience.
• Experience with decomposition techniques in stochastic optimization and their implementation in high performance computing environments.
• Demonstrated ability to design specialized algorithm approaches for challenging mathematical optimization problems.

Additional Information

#LI-Hybrid

Position Information

This is a Career Indefinite position, open to Lab employees and external candidates.

Why Lawrence Livermore National Laboratory?

• Included in 2024 Best Places to Work by Glassdoor!
• Flexible Benefits Package
• 401(k)
• Relocation Assistance
• Education Reimbursement Program
• Flexible schedules (*depending on project needs)
• Inclusion, Diversity, Equity and Accountability (IDEA) - visit https://www.llnl.gov/diversity
• Our core beliefs - visit https://www.llnl.gov/diversity/our-values
• Employee engagement - visit https://www.llnl.gov/diversity/employee-engagement

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 required to work in a Limited Area where you are not permitted to have a personal and/or laboratory mobile device in your possession. This includes, but not limited to cell phones, tablets, fitness devices, wireless headphones, and other Bluetooth/wireless enabled devices.

If you use a medical device, which pairs with a mobile device, you must still follow the rules concerning the mobile device in individual sections within Limited Areas. Sensitive Compartmented Information Facilities require separate approval. Hearing aids without wireless capabilities or wireless that has been disabled are allowed in Limited Areas, Secure Space and Transit/Buffer Space within buildings.

How to identify fake job advertisements

Please be aware of recruitment scams where people or entities are misusing the name of Lawrence Livermore National Laboratory (LLNL) to post fake job advertisements. LLNL never extends an offer without a personal interview and will never charge a fee for joining our company. All current job openings are displayed on the Career Page under “Find Your Job” of our website. If you have encountered a job posting or have been approached with a job offer that you suspect may be fraudulent, we strongly recommend you do not respond.

To learn more about recruitment scams: https://www.llnl.gov/sites/www/files/2023-05/LLNL-Job-Fraud-Statement-Updated-4.26.23.pdf

Equal Employment Opportunity

We are an equal opportunity employer that is committed to providing all with a work environment free of discrimination and harassment. All qualified applicants will receive consideration for employment without regard to race, color, religion, marital status, national origin, ancestry, sex, sexual orientation, gender identity, disability, medical condition, pregnancy, protected veteran status, age, citizenship, or any other characteristic protected by applicable laws.

We invite you to review the Equal Employment Opportunity posters which include EEO is the Law and Pay Transparency Nondiscrimination Provision.

Reasonable Accommodation

Our goal is to create an accessible and inclusive experience for all candidates applying and interviewing at the Laboratory. If you need a reasonable accommodation during the application or the recruiting process, please use our online form to submit a request.

California Privacy Notice

The California Consumer Privacy Act (CCPA) grants privacy rights to all California residents. The law also entitles job applicants, employees, and non-employee workers to be notified of what personal information LLNL collects and for what purpose. The Employee Privacy Notice can be accessed here.