Remote ML Materials Discovery Intern (R&D)

Sandia National Laboratories; California (MO); Remote; USD 52,000 - 68,000; Full time

Job summary

Sandia National Laboratories is seeking a year-round intern in ML-based materials discovery. The role focuses on applying machine learning and first principles simulations to accelerate materials discovery, with emphasis on inorganic materials and energy-related applications.

Remote work is possible within the U.S. The candidate will develop new featurization strategies, integrate ML with physics-based models, and communicate results to multidisciplinary teams.

Qualifications

• Earned bachelor’s degree.
• Currently attending full-time graduate program in science, engineering, or math.
• Minimum GPA guidance not specified.
• Ability to work up to 30 h/week in academic year and up to 40 h/week in summer.

Responsibilities

• Develop new material featurization strategies and apply ML/ DL to predict properties.
• Integrate ML outputs with physics-based models for thermodynamic/kinetic properties.
• Collaborate with multidisciplinary teams for experimental validation.
• Explore active learning to discover better materials.

Skills

Machine learning

Materials modeling

Interpretable ML

Scientific communication

Education

Bachelor's degree

Graduate program enrollment

Tools

LAMMPS

Pymatgen

ASE

Materials Project

Job description

Sandia National Laboratories is seeking a year-round intern in ML-based materials discovery. The role focuses on applying machine learning and first principles simulations to accelerate materials discovery, with emphasis on inorganic materials and energy-related applications.

Remote work is possible within the U.S. The candidate will develop new featurization strategies, integrate ML with physics-based models, and communicate results to multidisciplinary teams.