We have an opening for a computation-focused postdoctoral researcher to work in the areas of development of interatomic potentials and machine learned surrogate models to study and understand the behavior of materials at length and time scales not accessible in quantum simulations. You will be a creative force in the design, development, coding, fitting, testing and integration of these models into a framework that optimizes the process of generating interatomic potentials. This position is in the EOS & Materials Theory Group, Condensed Matter Section of the Physics Division.

This is a two-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.

Essential Duties
- Contribute to the conception, design, and execution of interatomic potentials and machine-learned, quantum-accurate surrogate models to address problems in the area of phase transitions in materials.
- Develop codes to fit different interatomic potential models and test their performance.
- Carry out quantum 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.

Qualifications
- PhD in physics, materials science, applied mathematics, engineering or related scientific field.
- Documented strong publication record in peer-reviewed journals.
- Experience in development of density functional theory codes or interatomic potentials or other atomistic/continuum methods.
- Ability to independently develop parallelized codes using Fortran, C/C++, Python.
- Experience with coding and use of linear, non-linear regression techniques, curve fitting methods, machine learning methods and/or uncertainty quantification.
- Experience in writing reports, publications and proposals.
- Proficient verbal and written communication skills as reflected in effective presentations at seminars, meetings and/or teaching lectures.
- Ability to work effectively independently, as well as in a team environment.

Desired Qualifications
- Experience with quantum simulations, LAMMPS simulation package to study material properties
- Knowledge of thermodynamics, phase transformations, defect structure and kinetics.

 

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.