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ARS Advanced Research Computing Innovation Fund (FY27)

Overview

The goal of the ARS Advanced Research Computing Innovation Fund is to enable cutting-edge ARS science by promoting the use of advanced research computing tools and methods in agricultural research.For FY2027, we expect to fund 4 to 6 proposals at up to $100,000 each, depending on availability of funds. Funds will likely be available for use some time in the first half of 2027 and will need to be spent or placed in collaborative agreements by the end of FY2027. For questions, contact Brian Stucky, SCINet computational biologist and acting ARS CSIO, or Heather Savoy, SCINet computational biologist (heather.savoy@usda.gov).

Deadline for proposal submission: Close of business on Friday, December 4, 2026.

Eligibility: ARS Category 1, 4, or 6 scientists with RL or supervisor approval. Please note that lead PIs on an FY2026 Innovation Fund award will not be eligible for an FY2027 award as lead PI.

Proposal guidelines and scope

Successful projects should:

  1. Have the development and/or application of advanced research computing methods to scientific research as a primary focus.
  2. Demonstrate that the project has a high probability of completion with impacts on an agricultural research question/problem.
  3. Utilize SCINet computing resources, including SCINet’s high-performance computing (HPC) clusters, Ceres and Atlas. These HPC systems are equipped with standard CPU nodes, graphics processing unit (GPU) nodes, and high-memory nodes. SCINet’s clusters support a wide range of research computing software and workflows, including industry-leading deep learning frameworks and containerization technologies.

Projects of high priority for funding are those that:

  1. Develop or adapt advanced research computing methods that empower ARS scientists to answer a specific question/problem or test a hypothesis of agricultural importance.
  2. Develop or adapt advanced research computing technologies to create a prototype digital product that solves a need for producers or agricultural researchers.

Researchers developing a method or digital product are encouraged to define a minimum viable product as a deliverable.

For this program, “advanced research computing” methods and technologies means the development and/or application of cutting-edge methods for data analysis, systems understanding and modeling, or automation that typically require advanced algorithms, large datasets, and substantial compute resources. Examples include:

  • machine learning (especially deep learning)
  • generative statistical modeling
  • machine reasoning and logic programming
  • knowledge representation
  • computer vision, including spatially aware image analyses
  • natural language processing, including text analysis and understanding
  • heterogeneous data fusion and integration
  • robotics and process automation

(Please note that these are examples and not inclusive of all possible methods and tools. Proposals using traditional statistical or process-based modeling methods, small-scale computing, or external computing resources are not likely to be competitive.)

Training, workshop, and working group activities are not supported by this call. Please see the SCINet web site for ways to get involved in these activities or contact the SCINet Office with questions (ARS-SCINet-Office@usda.gov).

For examples of successful proposal topics, please see the abstracts of proposals funded in FY2026, FY2024, FY2023, FY2022, and FY2021 (this program was paused for FY2025).

Proposal format and submission

All proposals must be submitted using the online submission form. The PI’s RL or supervisor must approve the proposal prior to submission (approval will be indicated on the submission form). (If the PI is an RL, their supervisor is still expected to approve the proposal. Any proposal listing the PI as the approver will not be considered for funding.) A complete application will include:

  • A proposal abstract of no more than 1,500 characters.
  • Proposal (project description) of up to 2 pages in length that clearly lays out a specific challenge or question, proposes a method or tool to be developed or applied to solve the challenge or to answer the question, and demonstrates that the research team has the capability to complete the project. Deliverables for the project should be defined.
  • A detailed project budget provided as an Excel spreadsheet. Please use REE budget form 455.
  • A budget justification of no more than 1,500 characters.

The proposal should be submitted as a PDF document with margins of no less than 1 inch and font size of no less than 11. The proposal may include figures, which should be included in the 2-page limit. References are not included in the 2-page limit for the proposal. Only one proposal as the lead investigator responsible for project completion can be submitted by a scientist, although a scientist can be a member of multiple proposal teams. We encourage teams of investigators collaborating on a problem.

Proposal review process

For the first step in the review process, each research office (RO) will review the proposals submitted from within the respective RO. Each RO will decide which of their proposals to advance for full panel review. After each RO has selected the proposals to advance for panel review, a review panel will be assembled that includes representation from all four ROs and the SCINet Office. Panelists will evaluate the strength of each proposal in five key areas:

  1. Scientific importance of the proposed project.
  2. Project feasibility (this is not meant to discourage high risk/high reward proposals – the question is about whether the research team will be able to carry out the work as proposed).
  3. Centrality of advanced research computing methods to the proposed work (i.e., are they a minor or major component?).
  4. Advanced research computing methods proposed (are they clear, appropriate, and realistic?).
  5. Quality of deliverables.
  6. Clarity of writing (is the proposal clear and understandable to a general scientific audience?).

The panel’s funding recommendations will be subject to final review and approval by ARS leadership. The total number of awards will depend on the availability of funds.