1,000+ Opportunities
Find the right grant
Search federal, foundation, and corporate grants with AI — or browse by agency, topic, and state.
The Lambda Research Grant program provides cloud GPU credits to qualifying academic researchers running AI/ML training, fine-tuning, evaluation, and inference workloads on Lambda's GPU cloud infrastructure (H100, H200, B200, and A100 instances). Grants up to $5,000 in compute credits per cycle. Open to academic researchers with institutional affiliation and an active AI/ML project.
Application requires brief project description, expected compute needs, anticipated publication/output, and willingness to acknowledge Lambda in resulting research. Lambda has expanded its Research Program in late 2024 to address the GPU access gap for academic AI researchers competing against industry labs with vastly larger compute budgets.
The program complements other compute grants (NVIDIA Academic Grant Program, AWS Cloud Credit for Research, NSF ACCESS) and is particularly accessible because of fast turnaround (typically days to weeks for decisions) and lower bureaucratic overhead. Lambda credits are usable on the Lambda Cloud, which provides per-second billing and access to multi-GPU instances suitable for distributed training.
Common funded research areas include foundation model fine-tuning, AI safety/alignment evaluations, computer vision research, multimodal models, and reinforcement learning.
Get a weekly digest of new grants like this
A free weekly digest of new foundation and federal funding opportunities as they're added to Granted. Unsubscribe anytime.
Or search similar grants →According to the current listing, eligibility includes: Academic researchers with institutional affiliation at a university, college, or accredited research institute. Must have active AI/ML research project with defined compute requirements. Open to faculty, postdoctoral researchers, and graduate students (with PI endorsement). Industry researchers and independent practitioners not eligible for the academic-tier grant (but Lambda offers separate startup credit programs). Confirm the full requirements in the official notice before applying.
The current listing shows up to $5,000 USD per researcher per cycle in Lambda GPU cloud credits (typically usable on H100, H200, B200, and A100 cloud GPUs). Larger research lab partnerships and multi-grant cycles available for high-impact projects. Verify award ceilings, matching requirements, and allowable costs in the official notice.
Lambda Labs Research Grant for Academic AI Researchers GPU Cloud Credits is funded by Lambda (Lambda Labs). Verify program details on the funder's official page before applying.
Start from the official opportunity page linked in this listing — it carries the sponsor's submission instructions.
Lambda offers qualifying researchers up to $5,000 in cloud credits to develop and showcase their work using Lambda's GPU cloud instances for AI and machine learning research, including training and fine-tuning of models. At CVPR 2026, Lambda announced an expansion of the program to cover entire research groups rather than only individual grants.
Lambda Research Grant Program for Cloud GPU Credits for AI and Machine Learning Researchers is sponsored by Lambda (Lambda Labs). Lambda offers qualifying researchers up to $5,000 in cloud credits to develop and showcase their work using Lambda's GPU cloud instances for AI and machine learning research, including training and fine-tuning of models.
Lambda's Research Grant Program gives AI/ML researchers direct access to GPU compute through up to $5,000 in Lambda Cloud credits, usable on on-demand GPU instances and 1-Click Clusters (NVIDIA B200, H100, A100, and more), along with mentoring from Lambda's Chief Scientific Officer. Announced to sponsor hundreds of researchers, the program was expanded at CVPR 2026 to cover entire research groups. Funded work is expected to target top venues such as NeurIPS, ICML, and ICCV. Applications are accepted on a rolling, competitive basis.
The Merck Stimulating Innovative Research Grant Program 2026 includes a dedicated grant topic for artificial intelligence in cell culture media and process development, offering up to EUR 150,000 per year for up to 3 years. The program accelerates innovation through collaborative research, early engagement with industry experts, and translation of novel ideas into practical solutions. In 2026, priority areas also include in-vitro models for neuroinflammatory diseases (EUR 250,000/year for 2 years) and innovative approaches to contaminated materials remediation (EUR 150,000/year for 2 years). The two-stage application process begins with non-confidential submissions, followed by deep-dive workshops where finalists collaborate with Merck scientists and managers to jointly optimize proposals. The AI-specific grant focuses on applying machine learning and AI to optimize cell culture media formulation, bioprocess parameter optimization, and manufacturing quality control.
The Sony Research Award Program is Sony's principal channel for funding external academic research, and the Focused Research Award is its collaborative track: up to 150,000 dollars for focused joint research between a university or research institute and Sony. The 2026 research areas are unusually broad for a corporate program and cover most of the modern AI stack alongside Sony's hardware interests - AI and large language models, computer vision, machine learning, robotics, human-computer interaction, affective computing, speech and language technologies, audio technologies, RF sensing, wireless communications, cybersecurity, sports technology, digital humans, generative AI, content creation and neural rendering, plus device-level areas including MicroLED and optical metasurfaces. For AI and robotics groups this makes it one of the wider corporate calls available, though the breadth is deceptive: Sony funds work that connects to its own research agenda, and proposals are strongest when there is an identifiable Sony research counterpart for the collaboration. Eligibility is tightly drawn around the principal investigator rather than the institution. The PI must be a full-time faculty member or researcher at a recognized institution - Assistant Professor, Associate Professor, Professor or equivalent researcher - and must be able to supervise PhD students. Co-PIs are permitted but must be from the same institution and meet the same requirements, which rules out the cross-institutional consortia common in public funding. The 2026 deadline is 15 September 2026 at 11:59pm Pacific, with a separate India-specific time given as 16 September 2026. Submission guidelines are on the Sony Research Award Program site.
The Meta Research PhD Fellowship supports doctoral students conducting research in areas central to Meta's technical agenda, with several of its annual award tracks dedicated to artificial intelligence and machine learning. Current AI-relevant tracks include AI System Hardware/Software Co-Design (high-performance AI algorithms spanning model compression, numerical optimization, benchmarking, and distributed inference and training), Applied Statistics (bias and variance estimation and correction in models and datasets, uncertainty quantification), AR/VR Human Understanding (efficient ML techniques that run on AR/VR devices), and Programming Languages (program synthesis, probabilistic and differentiable programming). Recipients receive two years of paid tuition and fees, a $42,000 annual stipend covering living expenses and conference travel, and a paid visit to Meta headquarters for the annual Fellowship Summit; the award carries no intellectual property claim on the student's research. The 2027 cycle opened August 3, 2026 with applications closing September 20, 2026, reference letters due in October 2026, and winners notified in January 2027.
NSF announced three more X-Labs topics on September 16, 2026 — Artificial Intelligence for Physical Systems is live, with Sequence to Function and Computation at the Limit of Physics coming this fall. The Q&A webinar is October 14 and an RFI on future topics closes October 30. The per-topic key-personnel restriction is what should be driving your team-building decisions.
Read articleNSF 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 articleOn July 22, 2026, the Department of Energy opened the first Phase I SBIR/STTR release tied to its Genesis Mission — roughly 40 awards across biotechnology, AI-for-quantum, predictable-materials design, and autonomous laboratories — alongside about $147M in FY25 Phase II funding. Here is what each topic area actually wants, who is eligible, how this connects to the $5B Genesis Mission, and how a small business should position before the broader fall solicitation.
Read article