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The Lambda Research Grant is one of the lowest-friction compute programmes available to AI researchers, and its usefulness comes from the combination of a modest award with an entirely rolling process and a very short application.
Qualifying researchers receive up to 5,000 US dollars in cloud credits toward Lambda's Instances product, which provides access to NVIDIA B200, H100, A100 and A6000 class GPUs among others, plus mentoring from Lambda's Chief Scientific Officer Chuan Li.
Lambda has said it expects to sponsor hundreds of researchers, which sets expectations correctly: this is a wide, shallow programme, not a competitive fellowship, and the realistic use case is a bounded experiment - fine-tuning, evaluation harnesses, ablation studies, small-scale pretraining - rather than a frontier training run.
Applications are accepted on a rolling basis with no published deadline, submitted through a Typeform linked from lambda. ai/research, which makes it a sensible first stop for a researcher who needs compute in weeks rather than the months a federal allocation or foundation grant requires.
The programme carries a visibility expectation: Lambda selects research to be featured on its website, and the grant is framed around developing and showcasing work using Lambda's platform, so applicants should be comfortable with their results being publicised and with the implicit expectation of attribution.
Lambda publishes little detail on eligibility criteria, specific GPU allocations or review timelines, so the fastest way to establish fit is simply to submit the form. For researchers who need substantially more compute, this pairs naturally with larger in-kind programmes such as the NAIRR Pilot allocations or NVIDIA's academic hardware grants rather than competing with them.
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Or search similar grants →According to the current listing, eligibility includes: Lambda describes the programme as open to qualifying researchers developing and showcasing work using Lambda's Instances platform, but publishes no detailed eligibility criteria - there is no stated restriction by country, institution type, career stage or academic affiliation on the page reviewed, and no requirement of a faculty principal investigator is stated. In practice the programme is aimed at AI researchers, including academic, independent and startup researchers, who need cloud GPU time to run experiments. The award is up to 5,000 US dollars in cloud credits redeemable only against Lambda's GPU cloud instances, together with mentoring from Lambda's Chief Scientific Officer, Chuan Li. No cash is provided and credits cannot fund personnel, equipment or indirect costs. Applications are accepted on a rolling basis with no published deadline and are submitted through a Typeform application linked from lambda.ai/research. Applicants should expect a showcase expectation: Lambda states that select research will be featured on its website, so results and attribution may be publicised. Because Lambda does not publish credit expiry terms, review timelines, renewal policy, GPU-type restrictions or any conditions on commercial use of outputs, prospective applicants should confirm those directly with Lambda before relying on the credits for a project with a fixed schedule. Researchers requiring compute beyond this scale should look to larger in-kind programmes such as the NAIRR Pilot resource allocations or vendor academic hardware grants. Confirm the full requirements in the official notice before applying.
The current listing shows the award is up to 5,000 US dollars in cloud credits redeemable against Lambda's Instances GPU cloud product. No cash is disbursed and credits cannot be applied to salaries, hardware purchase or overhead. amount_min is set to 0 because Lambda publishes no floor and describes the award as up to 5,000 dollars, so smaller allocations are made; amount_max is 5,000. In practical terms 5,000 dollars buys a meaningful but bounded amount of GPU time - on the order of a few thousand hours on mid-tier GPUs or a few hundred hours on current-generation accelerators such as the B200 or H100, depending on instance type and prevailing rates - which makes this a good fit for fine-tuning, evaluation runs, ablation studies and small-scale pretraining, and a poor fit for frontier-scale training. Lambda has stated an intention to sponsor hundreds of researchers, so the programme is designed for breadth of small awards rather than concentration. Verify award ceilings, matching requirements, and allowable costs in the official notice.
Lambda Research Grant Providing Cloud GPU Credits and Chief Scientist Mentoring to AI Researchers on a Rolling Basis is funded by Lambda (Lambda Labs, Inc.). 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.
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.
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