DOE Selects 29 Students for 2026-27 Computing Fellowship at 18 U.S. Universities
Updated
Updated · Newswise · Jun 17
DOE Selects 29 Students for 2026-27 Computing Fellowship at 18 U.S. Universities
1 articles · Updated · Newswise · Jun 17
Summary
Twenty-nine incoming fellows were chosen for the 2026-2027 DOE Computational Science Graduate Fellowship, a doctoral program focused on applying high-performance computing to research across fields from machine learning to physics and materials science.
The fellowship supports study at 18 U.S. universities and can be renewed for up to four years, covering stipend, tuition, fees and an annual academic allowance.
A required curriculum combines science and engineering, computer science, applied mathematics and HPC, plus a three-month practicum at one of 22 DOE-approved sites and an annual research meeting.
As of Sept. 1, the CSGF network will top 725 fellows and alumni from 87 Ph.D. institutions, with more than 500 alumni working in energy science, AI, quantum computing and nuclear stockpile stewardship.
Founded in 1991 and managed by the Krell Institute since 1997, the program is backed by DOE's Office of Science and the National Nuclear Security Administration to build U.S. leadership in supercomputing.
With science budgets cut but NNSA funding boosted, what is the future for research not tied to AI or nuclear security?
How will the new Office of AI and Quantum balance national security missions with open scientific discovery?
DOE CSGF 2026-27 Cohort: Strategic Investment in U.S. Computational Science Leadership
Overview
The DOE Computational Science Graduate Fellowship (DOE CSGF) selects its 2026-27 cohort to foster the next generation of computational scientists, who are essential for advancing national priorities. The fellowship program is structured around two tracks—Science and Engineering, and Mathematics & Computer Science—cultivating a broad spectrum of expertise. Science and Engineering fellows apply high-performance computing (HPC) to complex research problems, while Math/CS fellows develop broadly applicable methods and technologies that enhance computational science through HPC. Across both tracks, fellows increasingly integrate artificial intelligence and machine learning into their research, supporting innovation in computational science.