Operations Research Engineer - Computational Optimization
Organisation Name: LLNL
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Country: UnitedStates
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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 Laboratorys mission.
Pay Range
$103290- $159168 Annually
$103290 - $132612 Annually for the SES.1 level
$123960 - $159168 Annually for the SES.2 level
Please note that the pay range information is a general guideline only. Many factors are taken into consideration when setting starting pay including education experience the external labor market and internal equity.
Job Description
We have immediate openings for one or more Operations Research Engineers with a focus on Computational Optimization to conduct research in the areas of optimization with specific application to critical infrastructure systems. You will be an integral part of a multi-disciplinary team of researchers with skill sets ranging from computer and climate science to power and industrial engineering; projects are typically collaborative with partner academic institutions and other national labs. You will be formulating and solving advanced optimization models (typically including uncertainty and adversarial aspects) to address open problems in critical infrastructure operations planning and resilience. The ability to work closely with domain experts and end-users to characterize analyze and communicate inputs and solutions is critical in this role. Development of advanced mathematical optimization models (e.g. MIP formulations) and use of optimization solvers will be a primary technical focus. Solver extension and development (including heuristics) will likely be required to achieve scalability and run-time targets. This position is in the Computational Engineering Division (CED) at LLNL which resides within the broader Engineering Directorate. The research will be conducted in conjunction with LLNLs Cyber and Infrastructure Resilience (CIR) program.
In this roleyou will
Develop and extend mathematical programming (e.g. MIP NLP and MINLP) formulations of core critical infrastructure operations and planning optimization models.
Participate in research on the larger topics of infrastructure systems planning and operations and related optimization applications to develop and implement new state-of- the-art algorithms.
Present formal and informal overviews of research progress at group meetings.
Contribute to grant proposals and collaborate with others in a multidisciplinary team environment to accomplish research goals.
Pursue independent (but complementary) research interests and interact with a broad spectrum of scientists internal and external to the Laboratory.
Perform other duties as assigned.
Additional job responsibilities at the SES.2level
Support complex research projects with competing priorities and implement advanced research concepts in a multidisciplinary team environment where dedication and deadlines are important to project success.
Publish research results in external peer-reviewed scientific journals and participate in conferences and workshops.
Engage directly with sponsors and partners and participate in development of new program business.
Qualifications
Ability to secure and maintain a U.S. DOE Q-level security clearance which requires U.S. citizenship.
Bachelor's degree in Operations Research Engineering Computer Science Applied Mathematics or closely related field or the equivalent combination of education and related experience.
Experience formulating mathematical optimization models using algebraic modeling languages and/or commercial solver interfaces.
Fundamental knowledge of at least one widely used mathematical optimization solver (e.g. Gurobi CPLEX and Express).
Experience developing software in a high-level language such as Python Julia and C++ (Python preferred).
Analytical and problem-solving skills necessary to craft creative solutions to independently solve complex problems.
Sufficient verbal and written communication skills to collaborate effectively in a team environment present and explain technical information and document work.
Additional qualifications at the SES.2 level
Masters degree in the disciplines mentioned above.
Related industry experience in practical infrastructure (or related) optimization applications.
Proficient verbal and written communication skills and the ability to present and explain technical information to non-technical audiences.
Comprehensive knowledge of and broad experience with the application of mathematical optimization to critical infrastructure systems including electricity grid and natural gas networks.
Additional Information
All your information will be kept confidential according to EEO guidelines.
Position Information
This is a Career Indefinite position open to Lab employees and external candidates.
This position requires a Department of Energy (DOE) Q-level clearance.If you are selected wewill initiate a Federal background investigation to determine if youmeet 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.
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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.
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