Utilizing the Full Power of Empire AI Program

The Simons Foundation is accepting applications for the Utilizing the Full Power of Empire AI program, a competitive funding opportunity intended to advance cutting-edge mathematics and basic science research through the advanced computational capabilities of Empire AI. The foundation plans to support six to 12 proposals from the Empire AI research community. Successful proposals will present ambitious two-year research programs in computational astrophysics and physics, computational biology, mathematics, neuroscience, computational physical chemistry, or intersections among these areas. Each proposed project must rely on the development and utilization of foundational machine learning models to address problems of fundamental scientific importance. Projects must make substantive use of multinode clusters of GPUs available through Empire AI. Representative research areas that may benefit from these resources include computational biophysics, neuroscience, ecology and evolution, plant biology, optimal transport, multiscale physics, fluid dynamics and numerical general relativity. Every proposal must explain how the research will use multinode GPU clusters in Empire AI. Proposals centered on data curation or dataset creation may be considered only in exceptional cases and only when the resulting data will be used by the proposing investigators to solve scientific problems within the same proposal. The total program budget is expected to be $6 million over two years. There is no maximum budget for an individual award, and requested amounts should reflect the proposed research. Award amounts are inclusive of indirect costs, which are permitted subject to the foundation's indirect cost policy and nonnegotiable rate. No cost-sharing or matching requirement is stated. The lead Principal Investigator must hold a tenure-track or tenured faculty position at an eligible Empire AI consortium member institution: Columbia University, Cornell University, City University of New York, State University of New York, Rensselaer Polytechnic Institute, New York University, University of Rochester, Rochester Institute of Technology or Icahn School of Medicine at Mount Sinai. All applicants and key collaborators must hold a Ph.D., M.D. or equivalent degree and have a faculty position or equivalent appointment at a college, university, medical school or other research facility. Additional PIs may be based outside the Empire AI consortium through subcontracts, including at eligible U.S. and non-U.S. nonprofit organizations, public and private institutions, units of state and local government and eligible federal agencies. There are no citizenship requirements. Flatiron Institute employees may participate only as unfunded collaborators. Simons Foundation employees, including Flatiron Institute employees, cannot apply as PIs, and Foundation employees cannot receive project funding for individual expenses. Funding cannot be provided to institutions in China, including Hong Kong, their fiscal sponsors or agents, relevant subcontracts, or consultants residing or working for institutions there. Applications must be submitted through the Simons Award Manager, or SAM, under the applicant's own account. Applicants must complete their SAM profiles and provide required applicant and degree information, an ORCID iD, project title and dates, a proposal narrative using the SAM template, biosketches for the applicant and applicable additional personnel in SciENcv, NIH or NSF style, and a Resources and Research Environment document using the provided template. Applicants must disclose the extent and use of generative AI in developing the proposal, identify relevant affiliations with the Simons Foundation or Flatiron Institute, and provide a Data and Renewable Reagents plan when applicable. Applications also require institutional administrative contacts, including at least one Signing Official and one Financial Officer, all applicable project personnel, budgets and subcontract budgets where applicable, publications, current or pending other support, and applicable organizational assurances such as IRB, IACUC or biosafety approvals. Applicants must use the Check Application Progress function to identify and correct missing requirements before submission. A completed application must then be sent to the institutional Signing Official for electronic sign-off. The Signing Official's submission of the signature officially submits the application to the foundation; applications and individual application materials are not accepted by email or mail. Applications are reviewed by Simons Foundation scientific staff and an expert review committee. The source does not provide additional scored evaluation criteria. Changes after submission require contacting sfgrants@simonsfoundation.org, are permitted only before the deadline, and require the revised application to be sent for sign-off and signed again. Technical assistance is available at samsupport@simonsfoundation.org, with stated office hours Monday through Friday from 9 a.m. to 5 p.m. Applications opened September 1, 2026, and the full application deadline is December 1, 2026, at 12 p.m. noon Eastern time. No separate LOI, concept paper or other pre-application gating deadline is stated. Decision notifications are scheduled for March 1, 2027. Awards are scheduled to begin June 1, 2027, and the stated award duration runs through May 31, 2029. The source does not state that this funding opportunity recurs annually or on another regular schedule. The Simons Foundation may, for budgetary or other considerations, refer an application to The Simons Foundation International for consideration and funding; recipients funded by that entity remain subject to Simons Foundation policies and procedures, and additional terms may be included in the official award notification.

Clearly explain how the project will use multinode clusters of GPUs in Empire AI; demonstrate development and utilization of foundational machine learning models to solve problems of fundamental importance in an eligible scientific discipline; proposals focused on data curation or dataset creation should show that the resulting data will be used by the proposers to solve scientific problems within the same proposal; register and begin SAM early; complete applicant and personnel information before budgeting; allow ample time for corrections and institutional sign-off before the noon Eastern deadline