Science and Technology on a Mission!
For more than 60 years, the Lawrence Livermore National Laboratory (LLNL) has applied science and technology to make the world a safer place.
We have multiple openings for researchers to conduct basic and applied research in optimization techniques sequential decision making under uncertainty, on real world problems in healthcare, cyber security, and national security applications. These positions are in the Computational Engineering Division (CED), within the Engineering Directorate.
These positions will be filled at either the SES.1 or SES.2 level depending on your qualifications. Additional job responsibilities (outlined below) will be assigned if you are selected at the higher level.
- Work under general direction to implement algorithms for controlling simulations using approaches such as bandit optimization, black box optimization, evolutionary algorithms and model-based methods, stochastic control.
- Maintain a close interface with programmatic and project elements to ensure effective teamwork.
- Document efforts in technical reports and presentations.
- Contribute to the fulfillment of technical projects and organizational objectives as a member of a team.
- Perform other duties as assigned.
In Addition at the SES.2 Level
- Research, develop, and apply solutions to moderately complex optimization problems of programmatic interest.
- Publish papers in peer-reviewed journals and present results at scientific meetings and conferences.
- Bachelor’s degree in Computer Science, Computational Engineering, Applied Statistics, Applied Mathematics, Operations Research or related field, or the equivalent combination of education and related experience.
- Proficiency in one or more of the following optimization techniques: black-box optimization, evolutionary algorithms, model-based methods, stochastic control.
- Fundamental knowledge in the broad application of one or more higher level programming languages such as Python, Java, Matlab, R, Julia or C/C++.
- Experience with one or more modeling languages such as AMPL, GAMS, Pyomo, JuMP, and experience with one or more optimization solvers.
- Demonstrated ability to work independently under general direction within the scope of an assignment and use independent judgment in determining methods, techniques, and evaluation criteria.
- Sufficient verbal and written communication skills necessary to effectively collaborate in a team environment and present and explain technical information.
In Addition at the SES.2 Level
- Master’s degree in Computer Science, Computational Engineering, Applied Statistics, Applied Mathematics, Operations Research or related field, or the equivalent combination of education and related experience.
- Comprehensive knowledge and experience with modeling languages and optimization solvers.
- Proficient verbal and written communication skills necessary to effectively collaborate in a team environment and present and explain technical information and provide advice to management.
- PhD in Computer Science, Computational Engineering, Applied Statistics, Applied Mathematics, Operations Research or related field.
Pre-Employment Drug Test: External applicant(s) selected for this position will be required to pass a post-offer, pre-employment drug test.
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. In addition, all L or Q cleared employees are subject to random drug testing. Q-level clearance requires U.S. citizenship. If you hold multiple citizenships (U.S. and another country), you may be required to renounce your non-U.S. citizenship before a DOE L or Q clearance will be processed/granted.
Note: This listing has multiple openings; these are Career Indefinite positions. Lab employees and external candidates may be considered for these positions.
Lawrence Livermore National Laboratory (LLNL), located in the San Francisco Bay Area (East Bay), is a premier applied science laboratory that is part of the National Nuclear Security Administration (NNSA) within the Department of Energy (DOE). LLNL's mission is strengthening national security by developing and applying cutting-edge science, technology, and engineering that respond with vision, quality, integrity, and technical excellence to scientific issues of national importance. The Laboratory has a current annual budget of about $1.8 billion, employing approximately 6,500 employees.
LLNL is an affirmative action/ equal opportunity employer. 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, protected veteran status, age, citizenship, or any other characteristic protected by law.