2026 Computing Sciences Student Program at Lawrence Berkeley National Laboratory

Berkeley, California, United States -

Full Time

Start Date

Immediate

Expiry Date

03 Feb, 26

Salary

48.27

Posted On

05 Nov, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Computational Science, Computer Science, Data Science, Mathematics, High-Performance Computing, High-Speed Networking, Mathematical Modeling, Simulation, Numerical Algorithm Design, Quantum Computing, Data Analytics, AI/ML, Scientific Research, Software Development, Project Management

Industry

Research Services

Description

Spend Your Summer Learning and Earning at One of the World's Leading Centers for Computational Science! Berkeley Lab, located in Berkeley, CA, is a world leader in computing, biological, physical, materials, chemical, and energy sciences research. For students majoring in Computational Science, Computer Science, Data Science, Mathematics, and related fields, Berkeley Lab Computing Sciences hosts a 10–12 week research summer program that provides students with the opportunity to gain research experience. Participants will work on projects in areas such as computational research, high-performance computing, and high-speed networking, or at the interface of several disciplines, under the guidance of one or more staff members. This program is geared toward graduate students in any computing sciences-related discipline and undergraduate students between their junior and senior years who have completed core courses in Computer Science, Mathematics, or related areas of study. Projects are designed so that students will complete a significant portion of the work during the 10–12 weeks. The exact starting date is at the mutual convenience of the student and the needs of the program. Summer students will work on projects within one of the four divisions in the Computing Sciences Area: the Applied Mathematics and Computational Research Division, the Energy Sciences Network (ESnet), the National Energy Research Scientific Computing Center (NERSC), and the Scientific Data Division. Applied Mathematics and Computational Research Division The Applied Mathematics & Computational Research Division conducts research and development in mathematical modeling, simulation and analysis, numerical algorithm design, computer system architecture, quantum information science, quantum computing, computational science, computer science, and high-performance software. - Learn more about the Applied Mathematics & Computational Research Division Energy Sciences Network (ESnet) The Energy Sciences Network (ESnet) is a high-performance, unclassified network built to support scientific research. ESnet provides services to more than 50 U.S. Department of Energy research sites, including the entire National Laboratory system, its supercomputing facilities, and its major scientific instruments. ESnet's research focuses on advancing high-speed networks, integrating cloud and quantum technologies, applying AI/ML for smarter network management, automating complex workflows, and using data analytics to support large-scale science projects. - Learn more about ESnet - Learn more about specific projects available National Energy Research Scientific Computing Center (NERSC) The National Energy Research Scientific Computing Center (NERSC) is the primary scientific computing facility for the Office of Science in the U.S. Department of Energy. As one of the largest facilities in the world devoted to providing computational resources and expertise for basic scientific research, NERSC is a world leader in accelerating scientific discovery through computation. - Learn more about NERSC - Learn more about specific 2024 NERSC projects Scientific Data Division The Scientific Data Division (SciData) advances data-driven discovery by making scientific data a first-class, AI-ready asset. In partnership with the scientific community, methods and infrastructures are developed to support the full data lifecycle, from acquisition to long-term reuse, so that datasets remain trustworthy, interpretable, and usable across disciplines and applications. - Learn more about Scientific Data Division Requirements: Students must be enrolled in a full-time academic program at an accredited college or university. Proof of enrollment is required. Salary Range: The hourly range for this position is $18.67- $48.27. Pay will be dependent on the current level of education. Want to learn more about working at Berkeley Lab? Please visit: careers.lbl.gov Equal Employment Opportunity Employer: The foundation of Berkeley Lab is our Stewardship Values: Team Science, Service, Trust, Innovation, and Respect; and we strive to build community with these shared values and commitments. Berkeley Lab is an Equal Opportunity Employer. We heartily welcome applications from all who could contribute to the Lab's mission of leading scientific discovery, excellence, and professionalism. In support of our rich global community, all qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected categories under State and Federal law. Berkeley Lab is a University of California employer. It is the policy of the University of California to undertake affirmative action and anti-discrimination efforts, consistent with its obligations as a Federal and State contractor. Misconduct Disclosure Requirement: As a condition of employment, the finalist will be required to disclose if they are subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct, are currently being investigated for misconduct, left a position during an investigation for alleged misconduct, or have filed an appeal with a previous employer.

Responsibilities

Participants will work on projects in areas such as computational research, high-performance computing, and high-speed networking. They will complete a significant portion of the work during the 10–12 weeks under the guidance of staff members.