VerifiedInternship

High Performance Computing Graduate Student

HybridInternshipLos Alamos +1 morePosted 1h ago0 views
Salary
Not disclosed
Experience
0-2 Years
Work mode
Hybrid
Employment
Internship
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Job description

## About the Role Los Alamos National Laboratory’s High Performance Computing (HPC) Division is seeking recent graduates for a paid post‑graduate internship. The position offers mentorship, a challenging project, and the opportunity to present work to colleagues within a world‑class supercomputing environment. ## What You’ll Do - Contribute to research, development, and software engineering for petascale computing platforms. - Work on projects involving cluster computing, system administration, and large‑scale data management. - Develop and optimize code using languages such as C++, Python, SQL, and Perl. - Participate in parallel programming, FPGA programming, and Linux system management tasks. - Collaborate with interdisciplinary teams to solve cutting‑edge technical challenges in HPC. ## Required Qualifications - Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, Physics, or a related field. - Knowledge of or introductory experience with one or more of the following: cluster computing, system administration, C++/Python/SQL/Perl programming, Linux, parallel programming, FPGA programming, data storage, or computer networking. - Eligibility for Q clearance (U.S. citizenship required). - Ability to work on‑site part of the time (Hybrid work mode, within a 2‑hour commute of Los Alamos, NM). ## Benefits - Comprehensive medical, dental, and vision insurance. - 401(k) plan with 6% matching plus an additional 3.5% contribution. - Paid parental leave, flexible PTO, and tuition assistance. - On‑site gym, wellness programs, and extensive relocation assistance. - Opportunity to engage with cutting‑edge supercomputing research and a supportive scientific community.

Required skills

Job locations

Los AlamosUSA

Compensation

Salary for this role is not disclosed by the employer. We don’t have enough benchmark data from similar roles to produce a reliable estimate. The actual compensation will be discussed during the interview process.

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