Computational Modeling - Postdoctoral Researcher Staff Member
Physical Life Sciences | livermore, CA | 03/14/2023
Job Code: PDS.1 Post-Dr Research Staff 1
Organization: Physical and Life Sciences
Position Type: Post Doctoral
Security Clearance: None (however, 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
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 Laboratory’s mission.
We have an opening for a Postdoctoral Researcher to conduct research in the area of atomistic simulations and machine learning for polymeric systems under reactive and aging conditions. You will actively participate in the research of machine-learned (ML) interatomic models and use them to elucidate the complicated chemistry that ensues in the presence of environmental stressors (e.g., radiolysis, hydrolysis). You will also help further develop our machine learning framework and simulation capability. This position is in the Materials Dynamics and Kinetics group of the Materials Science Division.
- Perform and analyze first principles-based simulations (e.g., DFT, DFTB, etc.) to generate reference and validation data enabling ML interatomic model development.
- Develop ML models for reacting polymers including organic and siloxane-based systems and employ them in large scale simulations probing chemical evolution and long time and length scale chemistry.
- Refinement of a multi-scale workflow for determination of polymer degradation chemistry relevant to polymer aging experiments. This includes both radiolysis and heterogeneous hydrolysis studies.
- Development and maintenance of our advanced atomistic simulation codes for interatomic model optimization and simulation.
- Contribute to development of constitutive models from resulting data.
- Document research; write and publish papers in peer-reviewed journals, and present results within the DOE community, at working group meetings, and at conferences.
- Pursue independent but complementary research interests and interact with a broad spectrum of scientists internally and externally to the Laboratory.
- Perform other duties as assigned.
- PhD in Physics, Chemistry, Chemical Engineering, Materials Science, or a related field
- Experience with scientific code development, including programming in C++, C, and/or Fortran, or an equivalent level compiled language.
- Experience with large-scale simulations in high-performance computing environments and/or interatomic potential development.
- Ability to develop independent research projects through publication of peer-reviewed literature.
- Proficient verbal and written communication skills as reflected in effective presentations at seminars, meetings and/or teaching lectures.
- Self-motivated and excellent interpersonal skills with desire and ability to work in a collaborative, multidisciplinary team environment.
Qualifications We Desire
- Experience applying machine learning methods for problems in chemistry or materials science.
- Experience with large-scale simulations in high-performance computing environments.
- Experience with electronic structure calculations using packages such VASP, NWChem, or similar codes.
- Experience with molecular dynamics modeling of reactive systems.
Additional InformationAll your information will be kept confidential according to EEO guidelines.
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?
- Flexible Benefits Package
- Relocation Assistance
- Education Reimbursement Program
- Flexible schedules (*depending on project needs)
- Inclusion, Diversity, Equity and Accountability (IDEA) - visit https://www.llnl.gov/diversity
- Our core beliefs - visit https://www.llnl.gov/diversity/our-values
- Employee engagement - visit https://www.llnl.gov/diversity/employee-engagement
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.
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.
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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.