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Computational Modeling - Postdoctoral Researcher

Entry Level | Full-time
Postdoctoral/Fellowship | livermore, CA | 05/10/2022

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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 essential to innovation and creativity for continued success of the Laboratory’s mission.

Job Description

We have an opening for a Postdoctoral Researcher in computational modeling of energetic materials under detonation conditions. The position requires knowledge in the use of multi-physics simulation codes to help develop new reactive flow models for energetic materials. Additionally, this position requires knowledge to leverage physics-based modeling in conjunction with machine learning on material characterization data to extract meaningful features and predict relevant material properties and how they change with material aging. You will interact with a multidisciplinary team of computer scientists, materials scientists, and chemists. This position is in the Reaction Dynamics Group (RDG) within the Materials Science Division.

In this role you will

  • Contribute to the conception, design, and execution of research related to problems in multiscale modeling, materials aging, compatibility, and performance of energetic materials.
  • Conduct multi-physics numerical simulations based on ALE techniques to develop, validate, and verify current and new reactive flow energetic material models.
  • Utilize focused experiments and multi-scale modeling to improve material models, including mechanical strength of polymers and electromagnetic properties of metals.
  • Leverage machine learning and statistical techniques to determine relationships between material properties, performance, and/or aging.
  • Connect with experimentalists in order to improve current experiments as well as develop new techniques suited for probing shock phenomena.
  • Pursue independent but complementary research interests and interact with a broad spectrum of scientists internal and external to the Laboratory.
  • Present formal and informal overviews of research progress at regular meetings.
  • Document research; write and publish papers in peer-reviewed journals, and present results within the DOE community, at working group meetings, and at conferences.
  • Perform other duties as assigned.


  • Ability to secure and maintain a U.S. DOE Q-level security clearance with requires U.S. citizenship.
  • PhD in Materials Science, Chemical Engineering, Chemistry, Physics, or a related discipline.
  • Experience with explicit, finite-element or finite-difference codes.
  • Experience with machine learning and/or multivariant statistics.
  • Experience with high-level programming language (i.e., c/c++) and/or scripting language (i.e., Python/Perl).
  • Proficient verbal and written communication and interpersonal skills as reflected in published peer-reviewed papers and effective presentations at seminars, meetings, and/or teaching lectures.
  • Initiative and interpersonal skills with ability to work both independently and in a collaborative, multidisciplinary team environment.

Qualifications we desire

  • Experience in multi-scale simulation methodologies ranging from continuum to atom based electronic structure methods as applied to shocked energetic materials.
  • Experience in coupled electromagnetic-hydrodynamic simulations and/or experience developing multiphase models for equation of state, electrical conductivity for implementation in continuum models.
  • Experience processing variety of material characterization and performance data, e.g., X-ray CT, SEM, ultrasound, spectroscopic, etc.

Additional Information

All your information will be kept confidential according to EEO guidelines.

Position Information

This is a 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.

Why Lawrence Livermore National Laboratory?

  • Included in 2022 Best Places to Work by Glassdoor!
  • Work for a premier innovative national Laboratory
  • Comprehensive Benefits Package
  • Flexible schedules (*depending on project needs)
  • Collaborative, creative, inclusive, and fun team environment

Learn more about our company, selection process, position types and security clearances by visiting our Career site

COVID-19 Vaccination Mandate

LLNL demonstrates its commitment to public safety by requiring that all new Laboratory employees be immunized against COVID-19 unless granted an accommodation under applicable state or federal law. This requirement will apply to all new hires including those who will be working on site, as well as those who will be teleworking.

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.  For additional information, please see DOE Order 472.2

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.

Equal Employment Opportunity

LLNL is an affirmative action and equal opportunity employer that values and hires a diverse workforce. 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.

If you need assistance and/or a reasonable accommodation during the application or the recruiting process, please submit a request via our online form

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.

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