NSF Small Business Innovation Research (SBIR) Program - Environmental Technologies

The NSF Computer and Information Science and Engineering: Future Computing Research (Future CoRe) program (NSF 25-543) supports foundational computing research and education with a strong emphasis on AI and machine learning. The program funds research that advances the foundations of computing including AI/ML theory, algorithms, systems, and applications. Future CoRe supports small to medium-sized research projects that can have significant impact on computing foundations. The program has target dates of February 5, 2026 and September 10, 2026 for proposal submissions (note: these are target dates, not deadlines, meaning proposals may be submitted at any time but will be reviewed in batches around these dates). Investigators may not serve as PI, co-PI, or Senior/Key Personnel on more than two proposals submitted within any consecutive 12-month period across all Future CoRe programs. This is one of NSF's primary mechanisms for funding fundamental AI and machine learning research at U.S. academic institutions, covering areas such as machine learning theory, natural language processing, computer vision, robotics foundations, and human-AI interaction.

The ONR Long Range Broad Agency Announcement (N00014-25-S-B001) is the Office of Naval Research's primary mechanism for soliciting research proposals across all naval science and technology priority areas. The BAA accepts proposals on a rolling basis through September 30, 2026 and covers ONR's full spectrum of research interests with particular emphasis on AI-related topics including autonomous maritime systems, human-machine teaming, machine learning for sensor fusion, cooperative autonomous swarm technology, undersea autonomy, and AI-enabled decision superiority. Proposals can be funded through multiple mechanisms including individual investigator grants, the Young Investigator Program (~$510K over 3 years for early-career faculty), and Multidisciplinary University Research Initiative (MURI) awards ($1.5M/year for 3-5 years for research teams). ONR recommends contacting relevant program officers before submitting to discuss alignment with current research priorities. The BAA supports basic research (6.1), applied research (6.2), and advanced technology development (6.3) across the full range of naval-relevant science and engineering disciplines.

RFA-RM-27-015 funds a single Logistics Center as the coordinating hub of the NIH Common Fund's PRIMED-AI program, Precision Medicine with AI: Integrating Imaging with Multimodal Data. The award is a cooperative agreement, meaning substantial NIH scientific and programmatic involvement is built in rather than incidental, and it is administered by NIBIB on behalf of the Common Fund. The Center operates through three integrated cores: Administration, which runs the steering committees and develops consortium policies; Evaluation, which assesses progress across the funded portfolio; and Outreach, which maintains a web portal for sharing AI-based clinical decision support tools and facilitates engagement between researchers, clinicians and patient communities. The strategic point for applicants is that this is the only coordinating award in a multi-award program whose other components, the Data-to-Model Academic-Industrial Partnerships, Model-to-Clinic and Multi-use Frameworks Playbook RFAs, are separately competed and separately funded. The Logistics Center therefore does not generate its own AI models; it is scored on its capacity to run a consortium, set data and tool-sharing policy, and build infrastructure that makes other teams' clinical decision support tools discoverable and reusable. Applications are due by 5:00 PM local time of the applicant organization on the date specified for the relevant review cycle, with an earliest project start date of 2 October 2026 and a maximum project period of five years.

ERCAP (Energy Research Computing Allocations Process) allocates compute time on NERSC's Perlmutter supercomputer at Lawrence Berkeley National Laboratory, one of the world's largest GPU-based systems with over 7,000 NVIDIA A100 GPUs alongside AMD EPYC CPUs. ERCAP is the primary mechanism for the broader DOE Office of Science research community (and partner researchers) to access leadership-class GPU resources for AI/ML, foundation model training, scientific AI, climate AI, materials AI, and AI-coupled simulation. Annual allocation cycle: submissions typically open in August and close in early October, with allocations starting January 1 of the following year. The 2026-cycle ERCAP call closed October 8, 2026 for 2027 allocations. NERSC supports both pre-trained foundation model fine-tuning and pre-training campaigns, with a growing AI/ML user community. Recipients receive both compute hours and consultation from NERSC's NESAP for AI program providing hands-on optimization, MLOps support, and access to advanced features (interactive nodes, Jupyter at scale, ML-optimized storage). ERCAP complements DOE's INCITE (largest) and ALCC (mission-aligned) allocation pathways.