Machine Learning Physics Graduate Student

About the role#

The Equation of State Materials Theory Group is seeking graduate student interns to contribute to multidisciplinary research projects. These roles focus on the development of classical empirical and machine learning interatomic potentials, the discovery and numerical solution of partial differential equations (PDEs) to model material behavior at the continuum scale, and the analysis of large atomic datasets.

What you'll do#

• Develop parallel C, C++, and Python codes to train, test, and evolve PDEs for phase field and phase field crystal models.
• Create interatomic potentials derived from quantum simulations.
• Explore machine learning methods to discover and evolve models for material behavior.
• Analyze research results, provide weekly progress updates, and present findings at poster sessions.
• Review relevant literature, document technical results, and contribute to research papers.

What you'll need#

• Current enrollment as a graduate student in good standing at an accredited institution, pursuing a degree in Physics, Computer Science, Mathematics, Computer Engineering, or a related field.
• Proficiency in writing code using C, C++, and Python.
• A research background with a documented record of publication.
• Excellent written and verbal communication skills.
• Eligibility to access the Laboratory in compliance with Section 3112 of the National Defense Authorization Act (NDAA).

Location & details#

• Location: Livermore, California.
• Work Modality: This is a full-time, on-site position.
• Term: Rolling.