We have an opening for a Postdoctoral Researcher at Lawrence Livermore National Laboratory in Livermore, CA USA in the area of atomistic simulations and machine learning for materials under extreme conditions. This position will entail generation of machine-learned (ML) interatomic models and their use to elucidate the complicated thermochemistry (e.g., nanocarbon synthesis) that ensues. This involves continued software development of our machine learning framework and simulation capability. This position is in the Materials Dynamics and Kinetics group of the Materials Science Division. Note:  This is a two-year Postdoctoral appointment with the possibility of extension to a maximum of three years.

Essential Duties

• Develop ML models for reacting materials including organic mixtures and employ them in large scale simulations probing chemical evolution and long time and length scale chemistry.
• Development and maintenance of our advanced atomistic simulation codes for interatomic model optimization and simulation.
• Perform and analyze first principles-based simulations (e.g., DFT, DFTB, etc.) to generate reference and validation data enabling ML interatomic model development.
• Contribute to development of advanced thermochemical models from resulting data.
• Contribute to development of our ML interatomic model generation and simulation framework.
• 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.

Required Qualifications

• 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 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.
• Ability to develop independent research projects through publication of peer-reviewed literature.

Desired Qualifications

• Experience developing GPU-accelerated software, e.g., using Cuda, Kokkos, or RAJA
• 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.

To apply, please visit: https://us.smrtr.io/3JpB