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The NVIDIA Academic Grant Program is a compute-and-hardware award rather than a research grant, and treating it as the latter is the most common way applicants waste an application.
It provides up to 30,000 NVIDIA H100 80GB GPU hours of cloud compute, or physical hardware in the form of up to eight RTX PRO 6000 GPUs or two DGX Spark systems, alongside access to NVIDIA models and software distributions, letters of support that can be attached to other funding applications, and networking with NVIDIA researchers.
No cash changes hands, so salary, students and travel must be funded elsewhere - the grant removes the compute line from a budget, not the personnel line.
Proposals are accepted under three standing calls: simulation and modelling (scientific simulation, quantum computing, physics-informed machine learning); AI training and model development (generative AI training techniques, scaling approaches, custom model development); and AI inference, agents and systems software (generative AI customisation, compound AI systems, systems software for AI).
The binding technical condition is that the project must incorporate pretrained models from ai. nvidia. com or make extensive use of NVIDIA software distributions, and the proposed timeline must align with the GPU-hour availability window or hardware ship dates - a project that cannot start when the allocation lands is not fundable.
Previous winners must report results through the programme portal before reapplying. At the time of review NVIDIA's page stated the programme was not accepting new applications.
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Or search similar grants →According to the current listing, eligibility includes: Applicants must be full-time faculty members at accredited academic institutions that award research PhDs; submissions are accepted worldwide. Each proposal must address one of the programme's designated calls for proposals, follow the provided template precisely, incorporate pretrained models from ai.nvidia.com and/or make extensive use of NVIDIA software distributions, and demonstrate prior experience with NVIDIA technology. The project timeline must align with the expected GPU-hour availability dates and/or estimated hardware ship dates. Awards are in kind: up to 30,000 NVIDIA H100 80GB GPU hours, or up to eight NVIDIA RTX PRO 6000 GPUs or two NVIDIA DGX Spark systems, plus software and model access, letters of support and networking; no cash is provided. This is a competitive programme and not all projects meeting eligibility are accepted. Prior recipients must report results through the programme portal to be eligible to reapply. Applications are submitted at academicgrants.nvidia.com. NVIDIA's page stated at the time of review that the programme was not currently accepting new applications, and pointed prospective applicants to education discounts, open hackathons and the NVIDIA Inception startup programme in the interim. Confirm current call topics, allocation sizes and reopening dates directly with NVIDIA before preparing a submission. Confirm the full requirements in the official notice before applying.
The current listing shows this is an in-kind award, not cash. NVIDIA grants up to 30,000 NVIDIA H100 80GB GPU hours of cloud compute, or hardware in the form of up to eight NVIDIA RTX PRO 6000 GPUs or two NVIDIA DGX Spark systems, plus model and software access. amount_min of 25,000 and amount_max of 150,000 are ESTIMATES of the USD-equivalent value of these in-kind awards: the hardware track corresponds to roughly USD 25,000 at the low end (the related NVIDIA Academic Hardware Grant Program is documented at USD 5,000-25,000 in GPUs), while 30,000 H100 hours priced at prevailing commercial cloud rates lands in the low six figures. NVIDIA does not publish a dollar value for these grants and disburses no cash. Verify award ceilings, matching requirements, and allowable costs in the official notice.
NVIDIA Academic Grant Program for Researchers Providing GPU Cloud Hours and Hardware for Generative AI Training, Inference and Agentic Systems Research is funded by NVIDIA Corporation. 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 26-513 makes roughly $100 million available for up to 10 State and Regional AI Infrastructure Hubs at $4M to $12M each over five years. One award per state or multi-state region. One proposal per organization. And NSF is not buying you GPUs — it funds the coordination, the workforce and the faculty training, while the compute has to come from partners you have to already have.
Read articleThe OMAI project — led by AI2, funded by NSF and NVIDIA — will create fully open multimodal AI models for scientific research. For researchers priced out of commercial AI, this changes the equation.
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