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Postdoctoral Researcher -EOS & Materials Theory
Physical Life Sciences | livermore, CA | 10/13/2021
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 essential to innovation and creativity for continued success of the Laboratory’s mission.
We have an opening for a computation-focused Postdoctoral Researcher to work in the areas of development of machine-learned multi-scale surrogate models to study the evolution dynamical behavior of complex materials. You will be a creative force in the design, development, coding, fitting, testing and integration of these models into a framework that maps molecular dynamics simulations to multi-scale surrogate models. This position is in the EOS & Materials Theory Group, Condensed Matter Section of the Physics Division.
In this role you will
- Contribute to the conception, design, and execution of machine-learned multi-scale surrogate models to address problems in the area of solidifications and mechanical response in metals and alloys, as well as phase separation in mixed polymers.
- Develop codes to fit multi-scale time evolution models and test their performance.
- Carry out molecular dynamics simulations to generate dataset and calculate material properties.
- Present formal and informal overview of research progress at weekly meetings.
- Analyze, report, and present scientific results at seminars, technical meetings, national and international conferences.
- Publish research results in external peer-reviewed scientific journals.
- Perform other duties as assigned.
- PhD in materials science, physics, applied mathematics, mechanical engineering, or related scientific field.
- Documented publication record in peer-reviewed journals.
- Experience in development of materials simulation methods on the atomistic or continuum scale.
- Ability to independently develop parallelized codes using Python, C/C++, Fortran.
- Proficiency with modern deep learning platforms TensorFlow, PyTorch, and/or SkLearn
- Experience in writing reports, publications, and proposals.
- Proficient verbal and written communication skills as reflected in effective presentations at research seminars and meetings.
- Ability to work effectively independently, as well as in a team environment.
Qualifications We Desire
- Knowledge of theoretical physics and computational materials science, including thermodynamics, phase transformations, defect structure and kinetics.
- Scientific programming experience with materials computational tools such as VASP, LAMMPS, etc. to perform density functional calculations and molecular dynamics simulations.
- Experience with statistical learning methods, machine learning methods and/or uncertainty quantification.
Why Lawrence Livermore National Laboratory?
- Included in 2021 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.
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.
Pre-Placement Medical Exam
A job related pre-placement medical examination may be required.
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.
LLNS is committed to offering reasonable accommodations during the application and recruiting processes due to a disability. If you need assistance or an accommodation due to a disability, please submit a request via 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.