Vera C. Rubin Astronomy Frontiers Fellowship

The LSST Discovery Alliance gratefully acknowledges NVIDIA’s generosity in providing the funding for this Fellowship, and for providing the Vera C. Rubin Astronomy Frontiers Fellow with compute and NVIDIA training resources.

1. Program Overview

The LSST Discovery Alliance (LSST-DA) announces the Call for Applications for the inaugural Vera C. Rubin Astronomy Frontiers Fellowship.

The Vera C. Rubin Frontiers Fellowship will support an exceptionally promising postdoctoral-level scientist who will pioneer the innovative application of AI/ML methods to analysis of data from the NSF-DOE Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST). The Fellow will honor the legacy of Dr. Vera C. Rubin by conducting cutting-edge research using state-of-the-art computational infrastructure—specifically dedicated high-performance GPU hardware—while championing an inclusive, collaborative scientific culture.

2. Award Details & Resources

The Fellowship will provide salary, benefits, and a research allowance for two years through a grant to the Fellow’s chosen host institution:

• Stipend/Salary: $80,000 annually.
• Benefits: Full health insurance and employee benefits provided at the host institution’s standard postdoctoral rate.
• Research & Travel Allowance: $12,000 annually allocated for research-related expenses, including conference travel, publications, and computing supplies.
• Dedicated GPU Hardware Allocation: Guaranteed up to 20% reserved access to a dedicated NVIDIA DGX H200 8-GPU server hosted within the SLAC Shared Science Data Facility (S3DF), co-located with Rubin Observatory’s US Data Facility (USDF). Additional compute time may be requested via the Rubin Observatory Resource Allocation Committee (RAC).
• Training & Community Leadership: Full access to the NVIDIA Training Program, including instructor-led workshops and up to 100 self-paced NVIDIA Deep Learning Institute (DLI) course enrollments. The Fellow will dedicate up to 10% of their time engaging with the research community as an ambassador for AI-driven astrophysics across the scientific community and at NVIDIA public events.

3. Eligibility Criteria

• Degree: The Vera C. Rubin Astronomy Frontiers Fellowship is open to applicants who earned or will have earned their Ph.D. degree between January 1, 2019, and August 2027, in astronomy, physics, data science, or related disciplines. Fellowship funding will be released upon confirmation that the Ph.D. has been granted or that all conditions for its granting have been met.
• Career Stage: The opportunity is open to early-career/postdoctoral researchers demonstrating leadership potential in computational astrophysics, AI/ML methodologies, or big-data astronomy.
• Host Institution: The Fellowship is tenable at any eligible scientific or academic institution proposed by the applicant. The applicant must obtain written agreement from a faculty or scientific staff member to serve as mentor during the period of the Fellowship. The host institution must be able to accept awards without charging indirect costs ("overhead"). The awarding of this fellowship is contingent upon documented acceptance from the applicant’s host institution which must be received by the LSST Discovery Alliance prior to the formal award letter. Preliminary indications of acceptance may be submitted with the application, but they will not substitute for the required institutional documentation.
• The Fellowship is open to English-speaking citizens of all nations. All applicants will receive consideration without regard to race, creed, color, age, gender, gender identity or expression, sexual orientation, or national origin. Women and members of underrepresented groups are strongly encouraged to apply.
• Applicants must demonstrate that their research will be directly related to the Rubin Observatory’s Legacy Survey of Space and Time and that they can accelerate their LSST research through a substantial allocation on the NVIDIA GPU cluster at the Stanford/SLAC Shared Data Facility.

5. Important Dates and Deadlines

• September 15, 2026: Application website open
• November 2, 2026, 7:00 PM EST (4:00 PM PDT, 23:00 UTC): Applications due
• November 23, 2026, 7:00 PM EST (4:00 PM PST, 24:00 UTC): Letters of reference due only for candidates who advance to the next selection stage.
• February 1, 2027: Award offer made
• March 2027: Public announcement of Fellowship offer

6. Application Components & Submission Guidelines Applications must be submitted electronically via the LSST-DA Application Portal prior to November 2, 2026, 7:00 PM EST (4:00 PM PDT, 23:00 UTC):

A complete application package must include these materials in a single, pdf package:

• Curriculum Vitae: Including education, awards, and professional service.
• Publication List: Including key computational outputs/software packages.
• Research & AI Proposal (Up to 5 Pages):
• Summary of Prior Achievements: Overview of contributions to astronomical research, computational frameworks, or AI/ML applications.
• Proposed Research Plan: Description of the 2-year scientific program leveraging the Rubin-LSST data and dedicated NVIDIA DGX H200 GPU resources, including a quantitative estimate of total GPU server time needed.
• Community Engagement Plan: Proposal for championing inclusive practices, open science, and sharing AI/ML methodologies with the broader Rubin community.
• Letter of commitment from local mentor at the proposed host institution.
• Names and contact info for 3 Letters of Reference: Letters will be requested for candidates who advance to the final stage and should be e-mailed to agabela@lsst-da.org by November 23, 2026, 7:00 PM EST (4:00 PM PST, 24:00 UTC).

Evaluation Criteria

Candidates must meet the following requirements:

• A proven track record of data-intensive research in astronomy, specifically utilizing AI or machine learning. Direct relevance to or clear applicability for LSST is a plus.
• A compelling research project that effectively leverages the computational resources provided by this grant, including high-performance, AI-optimized GPU hardware and access to Rubin LSST data.
• Demonstrated experience in community engagement through organizing events (e.g., hackathons, workshops), developing educational resources (e.g., tutorials, documentation), or designing training activities along with a clear plan for broadening access to LSST data-intensive research.

Evaluation of candidates will be based on the following criteria:

• The originality and scientific merit of the proposed research project.
• The feasibility of the project and the candidate’s qualifications to execute it successfully.
• Full and promising use of the NVIDIA computing resources.
• The creativity, appropriateness, and potential impact of the community engagement proposal — particularly its capacity to reach a broad and diverse user base and meaningfully expand access to AI-driven scientific research with LSST data.

7. Contact Information & Program Inquiries

For questions regarding the Fellowship application process, please contact Ana Gabela at agabela@lsst-da.org.