AI Foundation models in science (GenAI4EU)

AI Foundation models in science (GenAI4EU) is sponsored by European Union (via Euro Access). This call emphasizes the use of advanced AI architectures, including multimodal generative AI, foundation models, and agentic AI, to deliver value across the entire industrial lifecycle.

AI Foundation models in science (GenAI4EU) Find EU-funding for your projects now! Search for Funding Search for programs Reset all filters Select the type of organisation that you are interested in to implement projects. The role of an organisation involved could by lead partner, regular project partner, associate partner, and observers.

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Selection of eligible entities Reset all EU Body An institution, body, office or agency established by or based on the Treaty on European Union and the Treaties establishing the European Communities. Education and training institution All education and training facilities for people of different age groups.

International organization An intergovernmental organization having legal personality under public international law or a specialized agency established by such an international organization. An international organization, the majority of whose members are Member States or Associated Countries and whose main objective is to promote scientific and technological cooperation in Europe, is an International Organization of European Interest.

Non-Profit Organisation (NPO) / Non-Governmental Organisation (NGO) An NPO is an institution or organization which, by virtue of its legal form, is not profit-oriented or which is required by law not to distribute profits to its shareholders or individual members. An NGO is a non-governmental, non-profit organization that does not represent business interests. Pursues a common purpose for the benefit of society.

Other Private institution, incl. private company (private for profit) A partnership, corporation, person, or agency that is for-profit and not operated by the government. Public Body (national, regional and local; incl.

EGTCs) Any government or other public administration, including public advisory bodies, at the national, regional or local level. Research Institution incl. University A research institution is a legal entity established as a non-profit organization whose main objective is to conduct research or technological development.

A college/university is a legal entity recognized by its national education system as a university or college or secondary school. It may be a public or private institution. Small and medium-sized enterprise (SME) A microenterprise, a small or medium-sized enterprise (business) as defined in EU Recommendation 2003/361 .

To qualify as an SME for EU funding, an enterprise must meet certain conditions, including (a) fewer than 250 employees and (b) an annual turnover not exceeding EUR 50 million and/or an annual balance sheet total not exceeding EUR 43 million. These ceilings apply only to the figures for individual companies.

Selection of eligible countries Reset all Belgium (Belgique/België) Bonaire, Saba, Sint Eustatius Bosnia and Herzegovina (Bosna i Hercegovina / Босна и Херцеговина) Faeroes (Føroyar / Færøerne) French Polynesia (Polynésie française/Pōrīnetia Farāni) French Southern and Antarctic Lands (Terres australes et antarctiques françaises) Greenland (Kalaallit Nunaat/Grønland) Israel (ישראל / إِسْرَائِيل) Kosovo (Kosova/Kosovë / Косово) New Caledonia (Nouvelle-Calédonie) North Macedonia (Северна Македонија) Saint Barthélemy (Saint-Barthélemy) Saint Pierre and Miquelon (Saint-Pierre et Miquelon) Switzerland (Schweiz/Suisse/Svizzera) Wallis and Futuna (Wallis-et-Futuna) Selection of topics Reset all Administration & Governance, Institutional Capacity & Cooperation Administration & Governance, Institutional Capacity & Cooperation This topic focuses on strengthening governance, fostering institutional capacity, and enhancing cross-border cooperation.

It includes promoting multilevel, transnational, and cross-border governance by designing and testing effective structures and mechanisms, as well as encouraging collaboration between public institutions on various themes. Innovation capacity and awareness are also key, with actions aimed at increasing the ability of individuals and organizations to adopt and apply innovative practices.

This involves empowering innovation networks and stimulating innovation across different sectors. Institutional cooperation and network-building play a crucial role, supporting long-term partnerships to improve administrative processes, share regional knowledge, and promote intercultural understanding.

This also includes cooperation between universities, healthcare facilities, schools, sports organizations, and efforts in management and capacity building. Agriculture & Forestry, Fishery, Food, Soil quality This topic focuses on strengthening the agricultural, forestry, and fisheries sectors while ensuring sustainable development and environmental protection.

It covers agricultural products (e.g., fruits, meat, olives), organic farming, horticulture, and innovative approaches to sustainable agriculture. It also addresses forest management, wood products, and the promotion of biodiversity and climate resilience in forestry practices.

In the food sector, the focus lies on developing sustainable and resilient food chains, promoting organic food production, enhancing seafood products, and ensuring food security and safety. Projects also target the development of the agro-food industry, including innovative methods for production, processing, and distribution.

Fisheries and animal management are essential aspects, with an emphasis on sustainable fishery practices, aquaculture, and animal health and welfare. This also includes efforts to promote responsible fishing, marine conservation, and the development of efficient resource management systems. Soil and air quality initiatives play a crucial role in environmental protection and public health.

This includes projects aimed at combating soil and air pollution, implementing pollution management systems, and preventing soil erosion. Additionally, innovative approaches to improving air quality—both outdoors and indoors—are supported, alongside advancing knowledge and best practices in soil and air management.

Air Quality, Biodiversity & Environment, Climate & Climate Change, Water quality & management This topic focuses on protecting the environment, promoting biodiversity, and addressing the challenges of climate change and resource management. It includes efforts to mitigate and adapt to climate change, develop low-carbon technologies, and reduce GHG emissions. Biodiversity promotion and natural protection are key aspects.

It also covers improving soil and air quality by reducing pollution, managing contamination, preventing soil erosion, and enhancing air quality both outdoors and indoors. Water management plays an essential role, including sustainable water distribution, monitoring systems, innovative wastewater treatment technologies, and water reuse policies.

Additionally, it addresses the protection and development of waterways, lakes, and rivers, as well as sustainable wetland management. Arts & Culture, Cultural Heritage, Tourism This topic focuses on preserving, promoting, and enhancing cultural and natural heritage in a sustainable way.

It includes efforts to increase the attractiveness of cultural and natural sites through preservation, valorisation, and the development of heritage objects, services, and products. Cultural heritage management, arts, and culture play a key role, including maritime heritage routes, access to cultural sites, and cultural services like festivals, concerts, and art workshops.

Tourism development is also central, with actions aimed at promoting natural assets, protecting and developing natural heritage, and increasing touristic appeal through the better use of cultural, natural, and historical heritage. It also covers the improvement of tourist services and products, the creation of ecotourism models, and the development of sustainable tourism strategies.

Circular Economy, Natural Resources This topic focuses on the sustainable management, protection, and valorisation of natural resources and areas, such as habitats, geo parks, and protected zones. It also includes preserving and enhancing cultural and natural heritage, landscapes, and protecting marine environments.

Circular economy initiatives play a key role, with actions aimed at innovative waste management, ecological treatment techniques, and advanced recycling systems. Projects may focus on improving recycling technologies, organic waste recovery, and establishing repair and re-use networks. Additionally, pollution prevention and control efforts address ecological economy practices, marine litter reduction, and sustainable resource use.

Competitiveness of Enterprises, Employment/Labour Market, SME & entrepreneurship This topic covers labour market development and employment, focusing on creating job opportunities, optimizing existing jobs, and addressing academic (un)employment and job mobility. It also includes attracting a skilled workforce and improving working conditions for various groups.

Strengthening small and medium-sized enterprises (SMEs) and boosting entrepreneurship are key priorities. This includes enhancing SME capacities, supporting social entrepreneurship, and promoting innovative business models.

Activities may focus on creating advisory systems for start-ups, spin-offs, and incubators, fostering business networks, and improving the competitiveness of SMEs through knowledge and technology transfer, digital transformation, and sustainable business practices.

Demographic Change, European Citizenship, Migration This topic focuses on fostering community integration and strengthening a common identity by promoting social cohesion, positive relations, and the development of shared spaces and services. It supports initiatives that enhance intercultural understanding and cooperation between different societal groups.

Digitalisation, Digital Society, ICT All projects where ICT has a significant role, including tailor-made ICT solutions in different fields, as well as digital innovation hubs, open data, Internet of Things; ICT access and connecting (remote) areas with digital infrastructure and services; services and applications for citizens (e-health, e-government, e-learning, e-inclusion, etc.); services and applications for companies (e-commerce, networking, digital transformation, etc.).

Disaster Prevention, Resilience, Risk Management This is about the mitigation and management of risks and disasters, and the anticipation and response capacity towards the actors regarding specific risks and management of natural disasters, for example, prevention of flood and drought hazards, forest fire, strong weather conditions, etc.. It is also about risk assessment and safety.

Education & Training, Children & Youth, Media This topic focuses on enhancing education, training, and opportunities for children, youth, and adults. It covers the expansion of educational access, reduction of barriers to education, and improvement of higher education and lifelong learning. It also includes vocational education, common learning programs, and initiatives supporting labour mobility and educational networks.

Additionally, it addresses the promotion of media literacy, digital learning tools, and the development of innovative educational approaches to strengthen knowledge, skills, and societal participation. This topic emphasizes the role of culture and media in education and social development. It supports initiatives that foster creativity, cultural awareness, and artistic expression among children and youth.

Activities include promoting cross-border cooperation in the audiovisual sector, enhancing digital content creation skills, and boosting the distribution of educational and cultural media products. Furthermore, it encourages the development of media literacy initiatives, helping young audiences critically engage with digital and media content.

By connecting education, creativity, and media, this topic strengthens cultural identity and supports inclusive, knowledge-based societies. Energy Efficiency, Renewable Energy This topic covers actions aimed at improving energy efficiency and promoting the use of renewable energy sources. It includes energy management, energy-saving methods, and evaluating energy efficiency measures.

Projects may focus on the energy rehabilitation and efficiency of buildings and public infrastructure, as well as promoting energy efficiency through cooperation among experienced firms, institutions, and local administrations. In the field of renewable energy, this encompasses the development and expansion of wind, solar, biomass, hydroelectric, geothermal, and other sustainable energy sources.

Activities include increasing renewable energy production, enhancing research capacities, and developing innovative technologies for energy storage and management. Projects may also address sustainable regional bioenergy policies, financial instruments for renewable energy investments, and the establishment of cooperative frameworks for advancing renewable energy initiatives.

Equal Rights, Human Rights, People with Disabilities, Social Inclusion This topic focuses on promoting equal rights and strengthening social inclusion, particularly for marginalized and vulnerable groups. It covers activities enhancing the capacity and participation of children, young people, women, elderly people, and socially excluded groups.

Activities can address the creation of inclusive infrastructure, improving access and opportunities for people with disabilities, and fostering social cohesion through innovative care services. It also includes initiatives supporting victims of gender-based violence, promoting human rights, and developing policies and tools for social integration and equal participation in society.

Health, Social Services, Sports This area focuses on improving health and social services, enhancing accessibility and efficiency for diverse groups such as the elderly, children, and people with disabilities. It includes the development of new healthcare models, innovative medical diagnostics and treatments (e.g., dementia, cancer, diabetes), and the management of hospitals and care facilities.

Additionally, activities addressing rare diseases, promoting overall wellbeing, and fostering preventive health measures fall under this theme. It also covers sports promotion, encouraging physical activity as a means to improve public health and social inclusion. Justice, Safety & Security This area focuses on strengthening justice, safety, and security through cross-border cooperation and institutional capacity-building.

It includes initiatives aimed at improving the efficiency and effectiveness of police, fire, and rescue services, enhancing civil protection systems, and rapid response capabilities for emergencies like chemical, biological, radiological, and nuclear incidents. Activities also target the prevention and combatting of organized crime, drug-related crimes, and human trafficking, as well as ensuring secure and efficient border management.

Furthermore, it covers initiatives promoting the protection of citizens, community safety, and the development of innovative security services and technologies. Mobility & Transport This area focuses on the development and improvement of transport and mobility systems, covering all modes of transport, including urban mobility and public transportation.

Actions aiming at improving transport connections through traffic and transport planning, rehabilitation and modernisation of infrastructure, better connectivity, and enhanced accessibility. Projects promoting multimodal transport and logistics, optimising intermodal transport chains, offering sustainable and efficient logistics solutions, and developing multimodal mobility strategies.

Also, initiatives establishing cooperation among logistic centres and providing access to clean, efficient, and multimodal transport corridors and hubs. Please leave this field blank The deadline for this call has expired.

AI Foundation models in science (GenAI4EU) Horizon Europe: Cluster 4 - Digital, Industry and Space HORIZON-CL4-INDUSTRY-2025-01-DIGITAL-61 Estimated EU contribution per project Funding Program Horizon Europe: Cluster 4 - Digital, Industry and Space Call number HORIZON-CL4-INDUSTRY-2025-01-DIGITAL-61 deadlines Opening 23. 09. 2025 17:00 Funding rate 100% Call budget € 30,000,000.

00 Estimated EU contribution per project € 6,000,000. 00 Link to the call ec. europa.

eu Link to the submission ec. europa. eu The purpose of this topic is to tap into their potential, and to advance the development of AI technology specifically tailored for the needs of science.

Foundation models in science are an evolving idea in the scientific community and go beyond the Generative AI trend. A foundation model can integrate information from various modalities of data. This model can then be adapted to a wide range of downstream, more specialized tasks.

To build downstream applications, the foundation model is fine-tuned with additional training and task-specific examples. Therefore, a foundation model is itself incomplete but serves as the common basis from which many task-specific models can be built via adaptation.

In science, such foundation models could be trained on data from a specific scientific field and then be fine-tuned for a variety of tasks and used by a wider community in the field.

Proposals should address one of the following scientific domains : (A) Materials science: the development of new, innovative and advanced materials is essential for EU’s economic security and for achieving a competitive and sustainable industry (especially sectors such as energy, mobility, construction, health and electronics).

Employing AI in the process of materials design, characteristics and discovery could significantly accelerate and scale potential innovative solutions. (B) Climate change science: advancing climate research is critical for achieving the EU's climate neutrality and resilience goals.

AI foundation models can contribute to more accurate insights into climate dynamics, enhanced predictions of extreme weather events, regional impacts and the evolution of climate tipping points. (C) Environmental pollution sciences: advancing environmental sciences can support the detection and characterisation of pollution sources, as well as their pathways, distribution and impacts to the environment and human health.

This is particularly relevant in the case of pollutants of concern, emerging and/or less known pollutants. (D) Agricultural sciences: advancing agricultural sciences research is critical to achieve a competitive, resilient and sustainable agricultural system. AI foundation models can contribute to enhance crop, livestock, soil and water management.

Proposals should focus on 1) developing foundation models (not limited to Generative AI) for science in the chosen domain; 2) showing a foundation model’s usefulness by adapting it to subtasks/scientific problems in the chosen domain; and 3) illustrating other possible areas of application.

The foundation models should provide researchers with access to essential AI-enabled capabilities for scientific discovery; employ the machine learning algorithms, models and architectures best suited for the chosen domain; be adaptable to different problems in the domain; and be based on a robust and reliable architecture, as any potential errors and problems would be propagated to the downstream applications.

The foundation models should be placed at the disposal of the scientific community as open models, including the source code and, where possible, training datasets and other associated assets needed for full reusability of the foundation models (unless justified otherwise).

This will serve a wider scientific community, thus broadening access to such scientific infrastructure and facilitating the use and adaptation of the model to different problems. Proposers should provide a clear documentation on the use and limitations of the model, alongside case studies demonstrating the model's application to a variety of tasks/problems in the chosen domain.

Multidisciplinary research activities should involve both AI and domain scientists, and address some of the following: Conceptualisation and planning: the scope, objectives and expected outcomes of the foundation model; Suitable interfaces for domain experts without computer science background to contribute to and utilise the outcomes; Data identification, collection and management of (preferably diverse, multimodal) datasets through semantically annotation data schemas; Model development, validation, testing under relevant operational and environmental conditions (such as thermal gradients, fatigue, corrosion, etc.) and, as appropriate, model evaluation and benchmarking, for example DOME; Integration of domain knowledge into the model (for example through machine readable representations like RDF (Resource Description Framework).

Expected effects and impacts Prove access to high quality (multimodal) data needed for the development of the model. If in the process of developing the model, there is a need to create new data sets or adapt existing ones, they should follow the FAIR principles. Describe the data curation and quality control procedures that will be used to ensure the accuracy, completeness, and consistency of the training data.

Contribute to efforts to reach common standards for data formats, metadata, taxonomies and ontologies. Demonstrate a strategy to access the computational resources needed for model training, evaluation/testing and inference.

Propose a model architecture that is designed with transparency in mind Ideally, employ methodologies for integrating domain/interdisciplinary knowledge into the model and seek synergies with solutions that facilitate the managing and making sense of vast amounts of data (for example knowledge graphs). Identify at least four possible use cases and scientific challenges that can be addressed with the model and its adaptations.

Identify and assess the potential risks of misuse of the foundation model. Propose a plan to make the model public, maintain and evolve it and promote it to the scientific community on a regular basis, in order to give visibility to the concept, discuss key findings and anticipate the technology evolution – possibly in synergy with other relevant projects.

Proposals should involve expertise in Social Sciences and Humanities (SSH), in the cases where legal and ethical experts should be involved to address data privacy, sharing agreements, and compliance with regulations. Synergies with the selected projects from HORIZON-INFRA-2025-01-EOSC-06: Using Generative AI (GenAI4EU) for Scientific Research via EOSC are encouraged, where relevant.

Proposals are encouraged to collaborate with established infrastructures such as the WeatherGenerator project. International cooperation is encouraged, where the EU has reciprocal benefit, like the Trillion Parameter Consortium. In this topic the integration of the gender dimension (sex and gender analysis) in research and innovation content is not a mandatory requirement.

Accelerate research and development in science, with focus on the domains of a) materials science, b) climate change science, c) environmental pollution science (including PFAS) and d) agricultural science ; Advance AI technology (not limited to Generative AI) tailored for scientific needs and potentially adaptable to other tasks in the area of application; Contribute to the development of foundation models in the areas of application, and pave the way for future funding of foundation models in a broader range of scientific disciplines; Advance solutions to societal or scientific challenges; Bridge existing knowledge gaps and induce interdisciplinarity by design across different fields necessary to advance the area of application; and Support open-source and open science, especially for research communities with limited access to modern AI tools.

short description The purpose of this topic is to tap into their potential, and to advance the development of AI technology specifically tailored for the needs of science. Call objectives Foundation models in science are an evolving idea in the scientific community and go beyond the Generative AI trend. A foundation model can integrate information from various modalities of data.

This model can then be adapted to a wide range of downstream, more specialized tasks. To build downstream applications, the foundation model is fine-tuned with additional training and task-specific examples. Therefore, a foundation model is itself incomplete but serves as the common basis from which many task-specific models can be built via adaptation.

In science, such foundation models could be trained on data from a specific scientific field and then be fine-tuned for a variety of tasks and used by a wider community in the field.

Proposals should address one of the following scientific domains : (A) Materials science: the development of new, innovative and advanced materials is essential for EU’s economic security and for achieving a competitive and sustainable industry (especially sectors such as energy, mobility, construction, health and electronics).

Employing AI in the process of materials design, characteristics and discovery could significantly accelerate and scale potential innovative solutions. (B) Climate change science: advancing climate research is critical for achieving the EU's climate neutrality and resilience goals.

AI foundation models can contribute to more accurate insights into climate dynamics, enhanced predictions of extreme weather events, regional impacts and the evolution of climate tipping points. (C) Environmental pollution sciences: advancing environmental sciences can support the detection and characterisation of pollution sources, as well as their pathways, distribution and impacts to the environment and human health.

This is particularly relevant in the case of pollutants of concern, emerging and/or less known pollutants. (D) Agricultural sciences: advancing agricultural sciences research is critical to achieve a competitive, resilient and sustainable agricultural system. AI foundation models can contribute to enhance crop, livestock, soil and water management.

Proposals should focus on 1) developing foundation models (not limited to Generative AI) for science in the chosen domain; 2) showing a foundation model’s usefulness by adapting it to subtasks/scientific problems in the chosen domain; and 3) illustrating other possible areas of application.

The foundation models should provide researchers with access to essential AI-enabled capabilities for scientific discovery; employ the machine learning algorithms, models and architectures best suited for the chosen domain; be adaptable to different problems in the domain; and be based on a robust and reliable architecture, as any potential errors and problems would be propagated to the downstream applications.

The foundation models should be placed at the disposal of the scientific community as open models, including the source code and, where possible, training datasets and other associated assets needed for full reusability of the foundation models (unless justified otherwise).

This will serve a wider scientific community, thus broadening access to such scientific infrastructure and facilitating the use and adaptation of the model to different problems. Proposers should provide a clear documentation on the use and limitations of the model, alongside case studies demonstrating the model's application to a variety of tasks/problems in the chosen domain.

Multidisciplinary research activities should involve both AI and domain scientists, and address some of the following: Conceptualisation and planning: the scope, objectives and expected outcomes of the foundation model; Suitable interfaces for domain experts without computer science background to contribute to and utilise the outcomes; Data identification, collection and management of (preferably diverse, multimodal) datasets through semantically annotation data schemas; Model development, validation, testing under relevant operational and environmental conditions (such as thermal gradients, fatigue, corrosion, etc.) and, as appropriate, model evaluation and benchmarking, for example DOME; Integration of domain knowledge into the model (for example through machine readable representations like RDF (Resource Description Framework).

Expected effects and impacts Proposals should: Prove access to high quality (multimodal) data needed for the development of the model. If in the process of developing the model, there is a need to create new data sets or adapt existing ones, they should follow the FAIR principles. Describe the data curation and quality control procedures that will be used to ensure the accuracy, completeness, and consistency of the training data.

Contribute to efforts to reach common standards for data formats, metadata, taxonomies and ontologies. Demonstrate a strategy to access the computational resources needed for model training, evaluation/testing and inference.

Propose a model architecture that is designed with transparency in mind Ideally, employ methodologies for integrating domain/interdisciplinary knowledge into the model and seek synergies with solutions that facilitate the managing and making sense of vast amounts of data (for example knowledge graphs). Identify at least four possible use cases and scientific challenges that can be addressed with the model and its adaptations.

Identify and assess the potential risks of misuse of the foundation model. Propose a plan to make the model public, maintain and evolve it and promote it to the scientific community on a regular basis, in order to give visibility to the concept, discuss key findings and anticipate the technology evolution – possibly in synergy with other relevant projects.

Proposals should involve expertise in Social Sciences and Humanities (SSH), in the cases where legal and ethical experts should be involved to address data privacy, sharing agreements, and compliance with regulations. Synergies with the selected projects from HORIZON-INFRA-2025-01-EOSC-06: Using Generative AI (GenAI4EU) for Scientific Research via EOSC are encouraged, where relevant.

Proposals are encouraged to collaborate with established infrastructures such as the WeatherGenerator project. International cooperation is encouraged, where the EU has reciprocal benefit, like the Trillion Parameter Consortium. In this topic the integration of the gender dimension (sex and gender analysis) in research and innovation content is not a mandatory requirement.

Accelerate research and development in science, with focus on the domains of a) materials science, b) climate change science, c) environmental pollution science (including PFAS) and d) agricultural science ; Advance AI technology (not limited to Generative AI) tailored for scientific needs and potentially adaptable to other tasks in the area of application; Contribute to the development of foundation models in the areas of application, and pave the way for future funding of foundation models in a broader range of scientific disciplines; Advance solutions to societal or scientific challenges; Bridge existing knowledge gaps and induce interdisciplinarity by design across different fields necessary to advance the area of application; and Support open-source and open science, especially for research communities with limited access to modern AI tools.

Regions / countries for funding EU Member States, Overseas Countries and Territories (OCT) Moldova (Moldova), Albania (Shqipëria), Armenia (Հայաստան), Bosnia and Herzegovina (Bosna i Hercegovina / Босна и Херцеговина), Canada, Faeroes (Føroyar / Færøerne), Georgia (საქართველო), Iceland (Ísland), Israel (ישראל / إِسْرَائِيل), Kosovo (Kosova/Kosovë / Косово), Montenegro (Црна Гора), New Zealand (Aotearoa), North Macedonia (Северна Македонија), Norway (Norge), Serbia (Srbija/Сpбија), Tunisia (تونس /Tūnis), Türkiye, Ukraine (Україна), United Kingdom EU Body, Education and training institution, Non-Profit Organisation (NPO) / Non-Governmental Organisation (NGO), Other, Private institution, incl.

private company (private for profit), Public Body (national, regional and local; incl. EGTCs), Research Institution incl.

University, Small and medium-sized enterprise (SME) To be eligible for funding, applicants must be established in one of the following countries: the Member States of the European Union, including their outermost regions the Overseas Countries and Territories (OCTs) linked to the Member States countries associated to Horizon Europe - see list of particpating countries Only legal entities forming a consortium are eligible to participate in actions provided that the consortium includes, as beneficiaries, three legal entities independent from each other and each established in a different country as follows: at least one independent legal entity established in a Member State; and at least two other independent legal entities, each established in different Member States or Associated Countries.

Any legal entity, regardless of its place of establishment, including legal entities from non-associated third countries or international organisations (including international European research organisations) is eligible to participate (whether it is eligible for funding or not), provided that the conditions laid down in the Horizon Europe Regulation have been met, along with any other conditions laid down in the specific call topic.

A ‘legal entity’ means any natural or legal person created and recognised as such under national law, EU law or international law, which has legal personality and which may, acting in its own name, exercise rights and be subject to obligations, or an entity without legal personality.

other eligibility criteria Affiliated entities (i.e. entities with a legal or capital link to a beneficiary which participate in the action with similar rights and obligations to the beneficiaries, but which do not sign the grant agreement and therefore do not become beneficiaries themselves) are allowed, if they are eligible for participation and funding.

Associated partners (i.e. entities which participate in the action without signing the grant agreement, and without the right to charge costs or claim contributions) are allowed, subject to any conditions regarding associated partners set out in the specific call conditions.

Entities which do not have legal personality under their national law may exceptionally participate, provided that their representatives have the capacity to undertake legal obligations on