1,000+ Opportunities
Find the right grant
Search federal, foundation, and corporate grants with AI — or browse by agency, topic, and state.
This listing may be outdated. Verify details at the official source before applying.
Find similar grantsFull proposal deadline is August 11, 2026, due by 5pm submitting organization's local time. The program runs every second Tuesday in August for FY24, FY25, and FY26. Award budget is up to $800,000 per award (exclusive of DOE national lab funding), durations up to 4 years, approximately 5 awards per
Correctness for Scientific Computing Systems (CS2) is sponsored by NSF Directorate for Computer and Information Science and Engineering (CISE). Supports research focused on correctness in scientific computing tools and tool chains.
Get alerted about grants like this
Get emailed when new opportunities from “NSF Directorate for Computer and Information Science and Engineering (CISE)” or related funders appear. Free, weekly, unsubscribe anytime.
Or search similar grants →Extracted from the official opportunity page/RFP to help you evaluate fit faster.
Correctness for Scientific Computing Systems (CS2) | NSF - U.S. National Science Foundation Correctness for Scientific Computing Systems (CS2) Important information for proposers and award recipients All proposals must be submitted in accordance with the requirements specified in the funding opportunity and in the Proposal & Award Policies & Procedures Guide (PAPPG) and its supplements .
All NSF grants and cooperative agreements are subject to the applicable set of NSF award terms and conditions . NSF has updated its research security policies for NSF funded projects. Supports research focused on correctness as it applies to scientific computing tools and tool chains, spanning low-level libraries through complex multi-physics simulations and emerging scientific workflows.
Supports research focused on correctness as it applies to scientific computing tools and tool chains, spanning low-level libraries through complex multi-physics simulations and emerging scientific workflows. Correctness for Scientific Computing Systems (CS 2 ) is a joint program of the National Science Foundation (NSF) and the Department of Energy (DOE).
The program addresses challenges that are both core to DOE’s mission and essential to NSF’s mission of ensuring broad scientific progress. The program’s overarching goal is to elevate correctness as a fundamental requirement for scientific computing tools and tool chains, spanning low-level libraries through complex multi-physics simulations and emerging scientific workflows.
At an elementary level, correctness of a system means that desired behavioral properties will be satisfied during the system’s execution.
In the context of scientific computing, correctness can be understood, at both the level of software and hardware, as absence of faulty behaviors such as excessive numerical rounding, floating-point exceptions, data races deadlocks, memory faults, violations of specifications at interfaces of system modules, and so on.
The CS 2 program puts correctness on an equal footing with performance, the focus of current scientific computing research. This program envisions the necessity of proving correctness even in performant scientific computing systems. Such correctness proofs themselves might rely upon multiple factors, including correctness of static and runtime program analyses.
Recognizing that many scientific computing applications are inherently statistical, use probabilistic or randomized algorithms, and/or deal with uncertain data, probabilistic notions of correctness may be needed. It is also critical to realize that correctness guarantees are provided with respect to some pre-defined system model.
For many reasons, including misspecification, approximation, and defect, the state space allowed by real systems might depart from that model. When this happens, the ability to probe the system to isolate the discrepancy is a key challenge in many domains. CS 2 requires close and continuous collaboration between researchers in two complementary areas of expertise.
One area is scientific computing, which, for this solicitation, is broadly construed to include: models and simulations of scientific theories; management and analysis of data from scientific simulations, observations, and experiments; libraries for numerical computation; and allied topics.
The second area is formal reasoning and mechanized proving of properties of programs, which, for this solicitation, is broadly construed to include automatic/interactive/auto-active verification, runtime verification, type systems, abstract interpretation, programming languages, program analysis, program logic, compilers, concurrency, stochastic reasoning, static and dynamic testing, property-based testing, and allied topics. hal.
finkel@science. doe. gov Awards made through this program Browse projects funded by this program Map of recent awards made through this program Directorate for Computer and Information Science and Engineering (CISE) Division of Computing and Communication Foundations (CISE/CCF) Office of Advanced Cyberinfrastructure (CISE/OAC)
Key questions and narrative sections extracted from the solicitation.
Research proposal addressing correctness as a fundamental requirement for scientific computing tools and tool chains
Close collaboration between scientific computing and formal reasoning/mechanized proving research areas
According to the current listing, eligibility includes: Universities, Nonprofits, State/local governments, For-profit organizations. Confirm the full requirements in the official notice before applying.
The current listing shows up to $800,000 per award. Verify award ceilings, matching requirements, and allowable costs in the official notice.
Applications for Correctness for Scientific Computing Systems (CS2) are due August 11, 2026. Build your timeline backwards from this date to cover registrations, approvals, and final submission checks.
Correctness for Scientific Computing Systems (CS2) is funded by NSF Directorate for Computer and Information Science and Engineering (CISE). Verify program details on the funder's official page before applying.
Yes — this listing is flagged as national in scope, so applicants across the U.S. may apply, subject to the sponsor's other eligibility criteria.
Applications go through the funder's official portal — the Apply Now link on this page goes there directly.
Economics of AI Fellowship is sponsored by Stripe. The fellowship supports foundational academic research in the economics of AI, an area currently understudied despite rapid technical progress in artificial intelligence. Fellows receive a baseline grant, opportunities to attend conferences with leading economists and technologists, and potential access to unique data via Stripe and its customers.
The UKRI Policy Fellowships 2025, funded by the Economic and Social Research Council, offer 18-month placements for academics to co-design research with UK government and What Works Network host organizations. Awards range from £180,000 to £280,000 and support three fellowship tracks: core policy fellows, Natural Hazards and Resilience policy fellows, and What Works Innovation fellows. Applicants must hold a PhD or equivalent research experience, be based at a UKRI-eligible UK organization, and possess relevant subject matter or methodological expertise. Government-hosted positions target early to mid-career academics, while What Works fellowships welcome all career stages. Fellows work directly with policymakers to bridge academic research and policy development on pressing national and global challenges. The application deadline is July 15, 2025.
NSF just committed $380 million to build a national network of AI-programmable, remotely operated laboratories — the Programmable Cloud Laboratories Test Bed (NSF 25-541), the agency's flagship contribution to the Genesis Mission. Twenty nodes, four years, self-driving experiments in chemistry, biology and materials. Here is what it funds, who is eligible, why the 'existing facilities only' rule matters, and how researchers and companies should position for what comes next.
Read articleNSF just put $83 million into six national-scale data systems through its Integrated Data Systems and Services program — the plumbing that makes AI-for-science actually work. Here is who won, how the three-category structure (national-scale, transition, planning) really functions, why the Category III planning grant is the on-ramp most teams should be aiming at, and how to build readiness before the next fourth-Tuesday-in-July deadline.
Read articleNSF's Growing Convergence Research program (NSF 24-527) offers up to $1.2 million in a two-year Phase I and up to $2.4 million more in a three-year Phase II — $3.6 million across five years — with a $16 million pool funding just 6 to 10 projects and a February 8, 2027 deadline. But GCR is not a bigger version of an interdisciplinary grant. It funds a specific team architecture, and the proposals that lose are usually the ones that mistake multidisciplinary collaboration for convergence. Here is what NSF actually means by convergence, how the two-phase gate works, and how to build a team that survives the Phase I review.
Read article