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We have an opening within the Energy Conversion and Storage Group for a Postdoctoral Research Staff Member. The Energy Conversion and Storage Group seeks to gain fundamental and practical insight into combustion processes through numerical simulations and experiments and develop predictive combustion models and software that are fast enough to impact the engine design cycle. This position is in the Computational Engineering Division (CED), within the Engineering Directorate.
- Conduct research in and development of one or more of the following areas: fluid dynamics, reactive chemistry, numerical methods, and heterogeneous computing.
- Design, implement, and analyze techniques in one or more of the above areas.
- Pursue complementary research interests and interact with a broad spectrum of scientists internally and externally.
- Reduce the time, resource cost, or increase accuracy of combustion simulations by designing efficient algorithms guided by applied mathematics and physics.
- Develop and apply numerical tools to simulate high efficiency clean combustion engine regimes and novel combustion systems by combining multidimensional fluid mechanics with chemical kinetics.
- Conduct detailed analysis of high efficiency clean combustion engine regimes and novel combustion processes.
- Collaborate with others in a multidisciplinary team environment to accomplish research goals.
- Publish research results in peer-reviewed scientific or technical journals and present results at external conferences seminars and/or technical meetings.
- Perform other duties as assigned.
- Recent PhD in Engineering, Applied Science, or related field.
- Experience in one or more of the following areas: fluid dynamics, reactive chemistry, numerical methods, and heterogeneous computing.
- Experience developing independent research projects, including publication of peer-reviewed literature.
- Comprehensive knowledge in analysis, modeling, and simulation tools (e.g. CFD, FEA).
- Ability to thrive autonomously; be pro-active in solving inevitable road blocks, have a persistent attitude, and self-train when necessary.
- Proficient verbal and written communication skills to collaborate effectively in a team environment and present and explain technical information.
- Interpersonal skills and ability to work in a collaborative, multidisciplinary team environment.
- Experience in writing technical reports, journal articles, and high-quality research proposals.
- Project management skills.
- Experience with C/C++, Python, Linux, GPUs, and parallel algorithm development.
Pre-Employment Drug Test: External applicant(s) selected for this position will be required to 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.
Security Clearance: None required.
However, if your assignment is longer than 179 days cumulatively within a calendar year, you must go through the Personal Identity Verification process. This process includes completing an online background investigation form and receiving approval of the background check. (This process does not apply to foreign nationals.)
Note: This is a one year Postdoctoral appointment with the possibility of extension to a maximum of three years. Eligible candidates are those who have been awarded a PhD at time of hire date.
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 $2.3 billion, employing approximately 6,900 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.