Postdoctoral Researcher in Large-Scale Atomistic Modeling

Lawrence Livermore National Laboratory

Entry Level | Full-time
Postdoctoral/Fellowship | livermore, CA | 03/15/2023

Reference #: REF3841O
Job Code: PDS.1 Post-Dr Research Staff 1
Organization: Physical and Life Sciences
Position Type: Post Doctoral
Security Clearance: None/Position does not require US citizenship (assignments longer than 179 days require a federal background investigation)
Drug Test: Required for external applicant(s) selected for this position (includes testing for use of marijuana)
Medical Exam: Not applicable
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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.


$108,840 Annually

Job Description

We have an opening for a Postdoctoral Researcher in the field of advanced large-scale atomistic materials modeling.  You will apply expertise at the intersection of materials science and data science to advance uncertainty-aware atomistic simulations of dynamic processes in materials. The successful candidate will plan, execute, and interpret very-large scale simulations on advanced high-performance computers and contribute to quantification of uncertainty in these models. This position is in the Quantum Simulations Group of the Materials Science Division.

In this role you will 

  • Contribute to a multidisciplinary team to advance methodologies for and applications of accurate, error-quantified atomistic materials simulations.
  • Contribute to evaluation of error-quantified materials property predictions using large-scale molecular dynamics simulations.
  • Develop, analyze, and/or apply models to quantify uncertainty in large-scale molecular dynamics simulations.
  • Maintain an awareness of technical literature in assigned areas.
  • Publish research results in external peer-reviewed scientific journals and participate in international conferences.
  • Present formal and informal overview of research progress at weekly meetings.
  • Pursue independent but complementary research interests and interact with a broad spectrum of scientists internally and externally.
  • Perform other duties as assigned.


  • PhD in Material Science, Theoretical Chemistry, Applied Mathematics, Physics, or a related field.
  • Experience in atomistic modeling of materials using molecular dynamics simulations, especially of solid-state dynamic processes and/or reacting molecular systems.
  • Knowledge in the one or more of the following additional areas:  computational electronic structure, interatomic potential development, machine learning/data science methodologies, massively-parallel computing, high-energy density or high-pressure science, visualization.
  • Experience with very-large scale (100M+ atoms) molecular dynamics simulations.
  • Experience authoring technical and scientific reports, delivering scientific presentations, and developing independent research projects through publication of peer-reviewed literature.
  • Ability to work independently on technical tasks, influence technical objectives, to provide in depth analysis, and develop unique technical solutions.
  • Proficient verbal and written communication skills as reflected in effective presentations at seminars, meetings and/or teaching lectures.
  • Initiative and interpersonal skills with desire and ability to work in a collaborative, multidisciplinary team environment.

Qualifications We Desire

  • Machine learning / data science applied to interatomic potential development and analysis.
  • Experience with electronic structure-based (ab initio) atomistic modeling methods, include density functional theory, quantum Monte Carlo, and/or quantum chemical methods.
  • Experience with active learning and/or interpretability of machine learned data representations, including neural networks, Gaussian process models, and other constructs.
  • Experience with parallel programming tools and software development for large-scale heterogeneous computers, including GPUs.

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, open to those who have been awarded a PhD at time of hire date.

Why Lawrence Livermore National Laboratory?

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.) 

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.

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.

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