EU enlists Nvidia to boost AI research across Europe

The European Commission has launched the AI in Science Enablers Initiative, with Nvidia joining the programme. The move connects industry support with Europe's research community through the RAISE framework.

Nvidia will provide tools, models, platforms, compute, cloud resources, data, training, technical support and collaborative projects for researchers, startups and the wider ecosystem.

The initiative aims to reduce barriers that can slow scientific work, particularly for smaller laboratories, early-career researchers and science-based startups. It highlights areas including climate modelling, molecular design, materials simulation and other research fields that rely on large-scale computing.

"Europe's ambition in AI in science can only become reality if we bring together the strengths of our research community, industry and other partners," said Ekaterina Zaharieva, European Commissioner for Startups, Research and Innovation. "Through the AI in Science Enablers campaign, we are turning this ambition into concrete commitments that give researchers access to the tools, expertise and resources they need to innovate."

Open models

A central part of Nvidia's contribution is a set of open source and open-access research resources. It has released more than 250 open models, 250 open datasets and more than 1,400 open source software projects across fields including large language models, healthcare, robotics, climate science, autonomous vehicles and scientific research.

These resources sit alongside scientific software and model families designed for biology, chemistry, weather, climate, energy, engineering, physics and materials science. Nvidia highlighted Nemotron, BioNeMo Agent Toolkit, PhysicsNeMo libraries, Earth-2 models and ALCHEMI NIM microservices as part of that offering.

Training push

Nvidia's Deep Learning Institute has also introduced an open source courseware hub with downloadable teaching materials on accelerated computing and deep learning. The material is openly licensed and available without enrolment fees or deadlines.

Its modular format allows the content to be adapted for university courses, supercomputing centre bootcamps and developer community teaching. That gives academic institutions and research centres a way to incorporate AI and computing training into existing programmes without building all materials from scratch.

Compute access

Another part of the effort focuses on access to computing infrastructure in Europe. Nvidia is working with cloud infrastructure partners and national AI factories in France, Spain and Sweden to widen access to European compute and services for startups and small and medium-sized enterprises.

Its Inception startup programme is one route for providing compute resources and technical support. AI2F in France has already worked with the Inception programme for four months, while the BSC AI Factory in Spain has moved from a pilot to its first full accelerator programme.

In Sweden, Sweden AI Factory has announced a collaboration with Nvidia to open infrastructure and expertise to startups and SMEs in sectors including life sciences, materials science, autonomous systems and gaming. EuroHPC supercomputing centres such as CINECA and JSC also provide academia and startups with free access to Nvidia GPU infrastructure and services for open research.

Nvidia is also offering office hours, bootcamps and hackathons to help researchers fine-tune models on their own datasets. The support is intended to address a common obstacle in scientific AI projects: access to hardware alone does not guarantee that teams can deploy and adapt models effectively.

Infrastructure scale

The announcement comes as Europe expands its AI computing estate. Nvidia said 35 supercomputers are in development across the continent, calling it the largest single-year expansion of supercomputing capacity in Europe.

According to Nvidia, those systems are expected to serve more than 3 million researchers across fields such as climate science, drug development and materials research. The figure underscores the scale of the buildout as European institutions seek to strengthen domestic research capacity and retain access to computing resources within the region.

The programme's design also shows how European policymakers are trying to connect public research goals with commercial technology suppliers, cloud operators, national AI factories and startup networks. Rather than focusing only on hardware procurement, the model combines software, data, skills and technical support with access to compute.

For research groups with limited budgets or in-house AI expertise, that broader package may prove as important as raw processing power. In practice, scientific use of AI often depends as much on training, model adaptation, data preparation and sustained engineering support as it does on access to machines.

By tying Nvidia's open software, startup support and training resources to the European Commission's framework, the initiative sets out a practical route for researchers and smaller companies to use AI tools within Europe's scientific system. It also puts greater emphasis on sovereign and regionally available compute as competition for advanced research infrastructure grows.