Paid Computational Science Grad Internship

Los Alamos National Laboratory; Los Alamos (NM); On-site; USD 30,000 - 39,000; Full time

Benefits offered by this job

Medical insurance (PPO or HDHP)

Dental and vision insurance

Life and disability insurance

Parental leave

Job summary

Los Alamos National Laboratory invites graduate students to participate in the Computational Science Graduate Student (GRA) Program, offering paid summer and year-round internships in Computer Science, Mathematics, and Statistics projects. The program provides mentoring, hands-on technical experience, and professional development through a structured work plan aligned with the student’s field of study.

Projects include computational earth science, computational physics, uncertainty

Qualifications

• Currently enrolled in an accredited graduate degree program in computer science, mathematics, or related field.
• Must be enrolled in at least 6 semester credit hours (or full-time equivalent).
• Entering graduate students must provide documentation of matriculation into an appropriate degree program.
• Cumulative GPA of at least 3.2 on a 4.0 scale (or equivalent).
• Desirable familiarity with scientific research methods and data.

Responsibilities

• Compute Earth Science simulations for subsurface, oceanic, and atmospheric systems.
• Improve simulations related to material and energy flows under extreme conditions.
• Develop and test mathematical methods to quantify predictive uncertainty of failures.
• Enhance reliability of supercomputing networks through fault analysis and task management.
• Explore quantum computing applications and test machine learning approaches on physical data.

Skills

Python

C++

Mathematics

Machine learning

Cybersecurity

Artificial intelligence

Communication

Job description

Los Alamos National Laboratory invites graduate students to participate in the Computational Science Graduate Student (GRA) Program, offering paid summer and year-round internships in Computer Science, Mathematics, and Statistics projects. The program provides mentoring, hands-on technical experience, and professional development through a structured work plan aligned with the student’s field of study.

Projects include computational earth science, computational physics, uncertainty