# Using Generative AI (GenAI4EU ) for Scientific Research via EOSC
EUACC page: https://www.euacc.ai/calls/HORIZON-INFRA-2025-01-EOSC-05
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## Public content

**topic id:** HORIZON-INFRA-2025-01-EOSC-05
**call id:** HORIZON-INFRA-2025-01
**title:** Using Generative AI (GenAI4EU ) for Scientific Research via EOSC
**programme:** Horizon Europe
**cluster:** INFRA
**status:** closed
**deadline date:** 2025-09-18T00:00:00+00:00
**deadline model:** single-stage
**start date:** 2025-05-06T00:00:00+00:00
**url:** https://ec.europa.eu/info/funding-tenders/opportunities/portal/screen/opportunities/topic-details/HORIZON-INFRA-2025-01-EOSC-05
**description:** Expected Outcome:
Project results are expected to contribute to the following outcomes:
• EOSC will make available the high-quality machine-readable scientific datasets to be consumed by machine-driven Generative AI applications at the service of science in line with the GenAI4EU[1] initiative and other key EU initiatives, like the Apply AI strategy.
• EOSC will facilitate the pooling and sharing of high-value data sets originated from EOSC and other data spaces identified as priorities (including, but not limited to, public sector, health, climate, environmental, manufacturing, agriculture, energy, financial and mobility data). The large-scale actions supported by EOSC will include the creation of common data platforms enabling secure and compliant sharing and reuse of sensitive, confidential, proprietary and personal data, as well as large-scale experimentation based on Generative AI, in line with the GenAI4EU initiative and other key EU initiatives, like the Apply AI strategy.
 Scope:
The scope of this call is to demonstrate and foster the use of Generative AI for Scientific Research, in line with the GenAI4EU initiative and other key EU initiatives, like the Apply AI strategy, throughout the research data lifecycle supported by EOSC. Generative AI can be used for activities such as writing, data generation and analysis, reporting and many others, for improving productivity. This enables lifting science beyond the human scale by facilitating the deployment and use of smart algorithms, machine learning and AI services onto the Web of FAIR Data. The awareness and readiness of using Generative AI for scientific research must be raised by training activities.
AI-powered natural language interfaces can transform the way researchers interact with open science infrastructures, how they discover and combine relevant data, software and application assets. EOSC should evolve towards offering such capabilities in ways that ensure unbiased and trustworthy responses. This includes adopting FAIR practices, for AI-trained models as well, to address challenges ranging from reproducibility to trustworthiness.
Open Data and Open Research Software are essential for reliable, trustworthy, and transparent GenAI. They ensure that datasets and algorithms are well-documented, accessible, and reproducible, enabling others to validate and understand GenAI algorithms. This transparency fosters trust, supports ethical standards, and ensures compliance with regulations, particularly important in the field of GenAI.
The proposals shall focus on all following aspects:
• Enrich the EOSC federation with Generative AI tools for evaluating research data quality, ensuring trustworthiness across the European network of trusted repositories, accessible by humans, machines, and Generative AI services: formulate protocols and policies to facilitate effortless data access, processing, and provenance updates within EOSC's repository and service network.
• Support European research infrastructures to improve the FAIRness of their data, so that they are ready to be combined with data of infrastructures in scientifically neighbouring domains, in order to provide Generative AI-ready data. • conduct pilots to validate the effectiveness and accuracy of the Generative AI-driven data quality evaluation methods, iteratively improving and refining them based on feedback and real-world use cases and removing the potential biases inherited from the training data.
 
• Run community engagement and support programmes for implementing Generative AI in scientific workflows via EOSC: • promote a sound training programme to facilitate the uptake and the use of Generative AI as a means to facilitate the FAIRification of data and data curation;
• demonstrate how Generative AI can facilitate quality assessment of FAIR data;
• advance the realization of machine-actionable (MA) research data and services, including AI-based systems;
• propose protocols and policies to govern automatic data workflows within the network of repositories and services.
 
 The proposals are expected to deliver on one or more of the following:
• Develop, promote and support real-life use cases for Generative AI models in scientific research domains, in line with the GenAI4EU initiative and other key EU initiatives, like the Apply AI strategy, such as: • augment datasets in scientific fields that rely on image analysis, such as biology, astronomy, and materials science: by generating synthetic images that closely resemble real data, researchers can expand their datasets, improve model robustness, share anonymized version of sensitive data and generalize better to unseen scenarios;
• learn the underlying patterns of complex time-series data, such as sensor readings in environmental monitoring or physiological signals in healthcare: by generating data samples that match the learned distribution, these models can detect anomalies or deviations from normal behaviour;
• accelerate materials design and discovery by predicting the properties of new materials without the need for extensive experimental testing: these models can generate novel material structures with desired properties, such as strength, conductivity, or catalytic activity, based on learned relationships between material compositions and properties;
• advance drug design and molecular modelling by generating novel molecular structures with desired pharmacological properties: these models can explore vast chemical spaces, predict the interactions between molecules and biological targets, and optimize drug candidates for efficacy and safety;
• simulate complex systems and phenomena in various scientific domains, such as physics, chemistry, and ecology: by capturing the underlying dynamics and interactions of the system, these models can generate realistic simulations that mimic observed behaviour or predict future outcomes under different conditions.
 
 The proposers should take into account and leverage on the results of relevant projects in the field, including AI4EOSC[2], iMagine[3], EOSC Data Commons[4], RI-SCALE[5], and other developments within the scope of the GenAI4EU initiative and other key EU initiatives, like the Apply AI strategy.
This topic implements the co-programmed European Partnership for the European Open Science Cloud.
Proposals could consider the inclusion of the European Commission's Joint Research Centre (JRC) research infrastructure in their research infrastructure portfolio for the creation and sharing or high-quality machine-readable scientific datasets to be consumed by machine-driven Generative AI applications. In this regard, the JRC will consider collaborating with any successful proposal.
null
Activities are expected to start at TRL 4 and achieve TRL up to 6 by the end of the project – see General Annex B.

[1] This call falls under the ‘GenAI4EU' initiative as in the Communication from the Commission to the European Parliament, the Council, the European Economic And Social Committee and the Committee of the Regions on boosting startups and innovation in trustworthy artificial intelligence ((COM(2024) 28 final of 24.1.2024).
[2] https://ai4eosc.eu/
[3] https://www.imagine-ai.eu/
[4] Grant no 101188179 from the call HORIZON-INFRA-2024-TECH-01
[5] Grant no 101188168 from the call HORIZON-INFRA-2024-TECH-01
**conditions:** General conditions
1. Admissibility Conditions: Proposal page limit and layout
described in Annex A and Annex E of the Horizon Europe Work Programme General Annexes.
Proposal page limits and layout: described in Part B of the Application Form available in the Submission System.

2. Eligible Countries
described in Annex B of the Work Programme General Annexes.
A number of non-EU/non-Associated Countries that are not automatically eligible for funding have made specific provisions for making funding available for their participants in Horizon Europe projects. See the information in the Horizon Europe Programme Guide.

3. Other Eligible Conditions
Subject to restrictions for the protection of European communication networks.

The Joint Research Centre (JRC) may participate as member of the consortium selected for funding.

described in Annex B of the Work Programme General Annexes.

4. Financial and operational capacity and exclusion
described in Annex C of the Work Programme General Annexes.

5a. Evaluation and award: Award criteria, scoring and thresholds
are described in Annex D of the Work Programme General Annexes.

5b. Evaluation and award: Submission and evaluation processes
The following additions to the general award criteria apply: The extent to which the proposed work incorporates the necessary coordination efforts and resources with other relevant projects and the EOSC governance structure in the context of the EOSC Partnership will be taken into account for Impact.

are described in Annex F of the Work Programme General Annexes and the Online Manual.

5c. Evaluation and award: Indicative timeline for evaluation and grant agreement
described in Annex F of the Work Programme General Annexes.

6. Legal and financial set-up of the grants
Beneficiaries will be subject to the following additional access rights:
• Each beneficiary must grant royalty-free access to its results to the EOSC Association for monitoring and developing policies and strategies for the European Open Science Cloud. Each beneficiary must also provide directly to the EOSC Association the information the beneficiary deems necessary for monitoring and developing policies and strategies for the European Open Science Cloud.
• Each beneficiary must grant royalty-free access to its intellectual property rights which are part of the results and are needed for further developing the European Open Science Cloud to legal entities identified by the granting authority and established in Member States or countries associated to the Horizon Europe Framework Programme. Such access rights are limited to non- commercial use.
 Beneficiaries must deposit the digital research data generated in the action in a trusted repository federated in the European Open Science Cloud (EOSC) in compliance with EOSC requirements.
Eligible costs will take the form of a lump sum as defined in the Decision of 7 July 2021 authorising the use of lump sum contributions under the Horizon Europe Programme – the Framework Programme for Research and Innovation (2021-2027) – and in actions under the Research and Training Programme of the European Atomic Energy Community (2021-2025)[[ This decision is available on the Funding and Tenders Portal, in the reference documents section for Horizon Europe, under ‘Simplified costs decisions’ or through this link: https://ec.europa.eu/info/funding-tenders/opportunities/docs/2021-2027/horizon/guidance/ls-decision_he_en.pdf]].
Grants awarded under this topic will be linked through collaboration agreements to the grants from following action:
HORIZON-INFRA-2025-01-EOSC-03: Advancing AI-readiness and Machine-Actionability in the EOSC Ecosystem.

described in Annex G of the Work Programme General Annexes.

Specific conditions
 described in the specific topic of the Work Programme

Application and evaluation forms and model grant agreement (MGA):
 Application form templates — the application form specific to this call is available in the Submission System
Standard application form (HE RIA, IA)
Standard application form (HE CSA) 
Evaluation form templates — will be used with the necessary adaptations&#xa0;
Standard evaluation form (HE RIA, IA)&#xa0;
Standard evaluation form (HE CSA)&#xa0;
Guidance
HE Programme Guide&#xa0;
Model Grant Agreements (MGA)
HE MGA&#xa0;
HE Unit MGA&#xa0;
Lump Sum MGA&#xa0;
Operating Grants MGA&#xa0;
Framework Partnership Agreement FPA&#xa0;
Call-specific instructions&#xa0;
Detailed budget table (HE LS)&#xa0;
Information on financial support to third parties (HE)&#xa0;
Information on clinical studies (HE)&#xa0;
Guidance: "Lump sums - what do I need to know?"

Additional documents:
 HE Main Work Programme 2025 – 1. General Introduction
HE Main Work Programme 2025 – 3. Research Infrastructures
HE Main Work Programme 2025 – 14. General Annexes
HE Programme Guide
HE Framework Programme 2021/695 
HE Specific Programme Decision 2021/764&#xa0;
EU Financial Regulation 2024/2509
Decision authorising the use of lump sum contributions under the Horizon Europe Programme
Rules for Legal Entity Validation, LEAR Appointment and Financial Capacity Assessment&#xa0;
EU Grants AGA — Annotated Model Grant Agreement&#xa0;
Funding & Tenders Portal Online Manual&#xa0;
Funding & Tenders Portal Terms and Conditions&#xa0;
Funding & Tenders Portal Privacy Statement
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**keywords:** HORIZON-INFRA-2025-01-EOSC-05, HORIZON-INFRA-2025-01, Artificial intelligence, Big data, Information systems
**last synced at:** 2026-11-09T17:23:17.403+00:00

## Review record

No independent verification record is available.

## Source metadata
