Automated Scientific Discovery (RAISE pilot) (RIA)

Overview

The EU funding opportunity is part of the Horizon Europe Programme, specifically targeting the Automated Scientific Discovery initiative under the HORIZON-RAISE-2027-01 call. This call is classified as a Research and Innovation Action (HORIZON-RIA) and involves a grant structure based on the HORIZON Action Grant Budget [HORIZON-AG]. The application process is single-stage, with submissions opening on September 22, 2026, and closing on February 2, 2027, at 17:00 Brussels time. The primary goal of this funding is to develop advanced closed-loop scientific experimentation systems that integrate automation and AI-driven decision-making in established laboratory settings. The initiative aims to enhance scientific discovery efficiency and productivity, promoting the retrofitting of labs with AI capabilities rather than complete redesigns. Funding specifics include a total budget of €29 million for approximately three projects, each receiving around €10 million. The focus areas include materials science, AI in science, and laboratory automation, encouraging collaborative proposals from interdisciplinary teams. The call emphasizes projects that create trustworthy AI systems capable of planning, executing, and analyzing experiments with minimal human intervention while ensuring ethical compliance. Successful proposals should demonstrate robust data management frameworks, AI-driven optimization mechanisms, and interdisciplinary collaboration among AI and domain scientists. The expected outcomes include prototype functional demonstrators showcasing the integration of advanced AI and automation in experimental processes. The initiative favors software development, although essential equipment can be purchased. Eligible participants include research institutions, universities, SMEs, and other entities from EU Member States and Associated Countries, with potential involvement from certain international collaborators. Co-funding is not mandatory, but applicants must showcase their financial viability. The proposal evaluation will be straightforward, requiring comprehensive submissions without preliminary rounds, and estimated success rates are projected between 10% and 39%, given the competitive nature of similar Horizon Europe calls. This initiative aligns with Horizon Europe's strategic aim to enhance Europe’s competitiveness in advanced technology sectors, focusing particularly on sustainable manufacturing and innovation in materials science.

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Highlights

The EU Funding Opportunity is part of the Horizon Europe Programme, specifically the AI in Science (HORIZON-RAISE-2027-01) call. It focuses on Automated Scientific Discovery (RAISE pilot) and is categorized as a HORIZON Research and Innovation Action (HORIZON-RIA). The type of Model Grant Agreement (MGA) is a HORIZON Action Grant Budget-Based [HORIZON-AG]. This is a forthcoming, single-stage application process. The planned opening date for submissions is September 22, 2026, and the deadline for submissions is February 2, 2027, at 17:00:00 Brussels time.

The expected outcomes of this funding opportunity include:the development of closed-loop scientific experimentation systems integrating automation with AI-driven decision-making in existing labs, accelerated scientific discovery with increased efficiency and reproducibility, improved scientific productivity, advancement of laboratory automation practices, and prototype functional demonstrators showcasing the integration of automation with AI.

The scope of the topic is the development of safe and trustworthy closed-loop scientific experimentation systems by integrating laboratory automation with AI-driven decision-making and robust data infrastructures. The projects aim to assist scientific labs with advanced automation and digitalization to design, develop, and test the intelligence layer that enables scientific instrumentation to plan, run, and analyze experiments semi- or fully autonomously. This should ideally occur in coordination with other labs and without requiring a complete redesign of existing laboratory setups.

Proposals should incorporate comprehensive data management systems for the collection, storage, processing, and sharing of experimental data. This includes developing scalable and secure data storage solutions, efficient data processing and analysis tools, and mechanisms for data sharing and collaboration across labs, while ensuring data security and privacy.

Systems may include AI-driven resource optimization modules to minimize energy, reagent, and material consumption during automated experimentation cycles. Systems should also incorporate an appropriate level of security and robustness by design.

Proposals should demonstrate how an existing lab can be retrofitted with AI-driven systems to plan, execute, and analyze experiments in a closed-loop fashion, incorporating human oversight and interaction to ensure accuracy, safety, and ethical compliance.

Possible research targets include, but are not limited to:Autonomous/semi-autonomous and adaptive AI systems (including agentic AI) that connect with laboratory instruments and robotics and can autonomously plan, act, learn and adapt within a scientific environment, within a validated safe pipeline. Assistive and interactive safe AI-managed robotic systems that automate diverse experiments and can be applied to a diverse hardware setup. Scalable automation solutions and networked AI systems that enable collaborative experimentation across multiple labs and networks of labs (including different geographic locations), supporting the simultaneous execution of large volumes of experiments. Systems that provide real-time data processing and analytics, enabling immediate feedback and dynamic adjustments during experiments. Standards and protocols to ensure interoperability between different laboratory instruments, robotics, and AI systems. Intuitive user interfaces for enhanced human-machine interaction. AI-driven predictive maintenance systems to optimize equipment uptime and resource utilization. Exploration of how scientific automation technologies can be adapted for use in various scientific disciplines beyond those in the scope of this call.

Proposals should demonstrate close interdisciplinary collaboration between computer/AI scientists and domain scientists. While the call prioritizes software development, it does not exclude the justified purchase of complementary equipment necessary to implement the research targets.

An initial focus is on materials science (Cluster 4). Impact areas of automated experimentation in this field could include drug discovery, battery technologies, photovoltaics, carbon capture/storage, water purification, soil remediation, environmentally friendly fertilizers, development of alternative protein sources in food production, and sustainable fabrics/dyes. The thematic focus can be expanded to include scientific disciplines and experimental settings of interest to collaborating clusters. International collaboration is encouraged. Proposals are expected to develop synergies with running Horizon Europe projects in the same field, such as HORIZON-CL4-INDUSTRY-2025-01-DIGITAL-61.

Regarding general conditions, admissibility conditions related to proposal page limits and layout are described in Annex A and Annex E of the Horizon Europe Work Programme General Annexes and Part B of the Application Form in the Submission System. Eligible countries are described in Annex B of the Work Programme General Annexes, with specific provisions for non-EU/non-Associated Countries detailed in the Horizon Europe Programme Guide. Other eligible conditions are described in Annex B, and financial and operational capacity and exclusion are described in Annex C of the Work Programme General Annexes. Evaluation and award criteria, scoring, and thresholds are described in Annex D. Submission and evaluation processes are described in Annex F of the Work Programme General Annexes and the Online Manual. The indicative timeline for evaluation and grant agreement is described in Annex F, and the legal and financial setup of the grants is described in Annex G of the Work Programme General Annexes. Specific conditions are described in the specific topic of the Work Programme.

Application and evaluation forms and the Model Grant Agreement (MGA) are available. Application form templates are in the Submission System, including the standard application form (HE RIA, IA). Evaluation form templates, which will be adapted as necessary, include the standard evaluation form (HE RIA, IA). Guidance is provided in the HE Programme Guide, and the Model Grant Agreement is the HE MGA. Call-specific instructions, information on financial support to third parties, and information on clinical studies are also available.

Additional documents include the HE Main Work Programme 2026-2027 sections on General Introduction, Digital, Industry and Space, Horizontal Activities, and General Annexes, as well as the HE Programme Guide, HE Framework Programme 2021/695, HE Specific Programme Decision 2021/764, EU Financial Regulation 2024/2509, the Decision authorising the use of lump sum contributions under the Horizon Europe Programme, Rules for Legal Entity Validation, LEAR Appointment and Financial Capacity Assessment, EU Grants AGA, Funding & Tenders Portal Online Manual, Funding & Tenders Portal Terms and Conditions, and Funding & Tenders Portal Privacy Statement.

The budget overview includes two topics for the year 2027. HORIZON-RAISE, a HORIZON-RIA, has a budget of €29,000,000 and is a single-stage action with an opening date of September 22, 2026, and a deadline of February 2, 2027. It is expected to fund around 3 grants with contributions around €10,000,000. HORIZON-RAISE-2027-01-02, also a HORIZON-RIA, has a budget of €3,000,000, is a single-stage action with the same opening and deadline dates, and is expected to fund 1 grant with contributions around €3,000,000.

There are partner search announcements available, and LEARs, Account Administrators, and self-registrants can publish partner requests on the portal. The submission system is planned to open on the date stated in the topic header.

Support is available through the Online Manual, Horizon Europe Programme Guide, Funding & Tenders Portal FAQ, Research Enquiry Service, National Contact Points (NCPs), Enterprise Europe Network, IT Helpdesk, European IPR Helpdesk, CEN-CENELEC Research Helpdesk, ETSI Research Helpdesk, the European Charter for Researchers, and Partner Search.

In summary, this Horizon Europe funding opportunity aims to advance scientific discovery by developing and implementing AI-driven, automated experimentation systems in existing laboratories. It encourages interdisciplinary collaboration and focuses on software development, with an initial emphasis on materials science. The goal is to create safe, trustworthy, and efficient research environments that can accelerate scientific progress across various disciplines. The call provides funding for research and innovation actions (RIA) with two distinct budget allocations, and it offers extensive support and guidance for applicants through various resources and networks.

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Breakdown

Eligible Applicant Types:The eligible applicant types are not explicitly stated, but based on the nature of Horizon Europe Research and Innovation Actions (RIA), eligible applicants typically include universities, research institutes, SMEs, large enterprises, and other legal entities capable of conducting research and innovation activities. Given the encouragement of international collaboration, entities from non-EU/non-Associated Countries may also be eligible under specific provisions.

Funding Type:The funding type is a grant, specifically a HORIZON Action Grant Budget-Based [HORIZON-AG], as indicated by the Type of MGA (Model Grant Agreement). The action is a HORIZON Research and Innovation Action (HORIZON-RIA).

Consortium Requirement:While not explicitly stated, the call encourages collaboration across multiple labs and networks of labs, suggesting that a consortium of multiple applicants is preferred, although single applicants might be eligible if they can demonstrate the necessary capabilities.

Beneficiary Scope (Geographic Eligibility):The geographic eligibility includes EU member states and associated countries as described in Annex B of the Work Programme General Annexes. The opportunity also mentions that 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.

Target Sector:The target sector is multidisciplinary, focusing on AI in Science, laboratory automation, and data infrastructure. It has an initial focus on materials science (Cluster 4) but can be expanded to include scientific disciplines and experimental settings of interest to collaborating clusters. Specific areas mentioned include drug discovery, battery technologies, photovoltaics, carbon capture/storage, water purification, soil remediation, environmentally friendly fertilizers, development of alternative protein sources in food production, and sustainable fabrics/dyes. The call also targets software development and the integration of AI with laboratory instruments and robotics.

Mentioned Countries:The opportunity mentions EU member states and associated countries, as well as non-EU/non-Associated Countries that have made specific provisions for funding participants in Horizon Europe projects.

Project Stage:The expected maturity of the project is research and development, leading to demonstration. The call aims to fund projects that will design, develop, and test the intelligence layer for scientific instrumentation and retrofit existing labs with AI-driven systems. The expected outcome includes prototype functional demonstrators.

Funding Amount:The funding amounts vary by topic. HORIZON-RAISE has a budget of €29,000,000 with an indicative contribution of around €10,000,000 per grant and HORIZON-RAISE-2027-01-02 has a budget of €3,000,000 with an indicative contribution of around €3,000,000 per grant.

Application Type:The application type is an open call with a single-stage submission process.

Nature of Support:Beneficiaries will receive money in the form of a grant to support their research and innovation activities.

Application Stages:The application process is single-stage.

Success Rates:The success rates are not explicitly mentioned, but given the competitive nature of Horizon Europe calls, the success rate is likely to be below 10%.

Co-funding Requirement:The co-funding requirement is not explicitly mentioned, but Horizon Europe projects typically require a certain level of co-funding, which is detailed in the relevant program guidelines and annexes.

Summary:

This Horizon Europe call, under the AI in Science initiative (HORIZON-RAISE-2027-01), aims to foster the development of safe and trustworthy closed-loop scientific experimentation systems. The goal is to integrate laboratory automation with AI-driven decision-making processes and robust data infrastructures, ultimately accelerating scientific discovery and improving scientific productivity. The call targets scientific labs with an advanced level of automation and digitalisation, encouraging them to design, develop, and test the intelligence layer that enables scientific instrumentation to operate semi- or fully autonomously.

The funded projects are expected to incorporate comprehensive data management systems, AI-driven resource optimisation modules, and demonstrate how existing labs can be retrofitted with AI-driven systems. The call prioritizes software development but does not exclude the purchase of complementary equipment. While there is an initial focus on materials science, the thematic scope can be expanded to include other scientific disciplines. International collaboration is encouraged, and proposals are expected to develop synergies with existing Horizon Europe projects.

The call includes two specific topics:HORIZON-RAISE with a budget of €29,000,000 and HORIZON-RAISE-2027-01-02 with a budget of €3,000,000. The application process is single-stage, with a planned opening date of September 22, 2026, and a deadline of February 2, 2027. Applicants are advised to consult the Horizon Europe Programme Guide and the Funding & Tenders Portal Online Manual for detailed guidance on eligibility, evaluation criteria, and submission procedures.

Short Summary

Impact

The funding aims to develop safe and trustworthy closed-loop scientific experimentation systems that integrate laboratory automation with AI-driven decision-making, ultimately accelerating scientific discovery and improving scientific productivity.

Applicant

Applicants should possess expertise in AI, automation, and scientific research, with a focus on interdisciplinary collaboration between computer/AI scientists and domain scientists.

Developments

The funding will support projects in the area of automated scientific discovery, specifically targeting the integration of AI with laboratory automation and data infrastructures.

Applicant Type

This funding is designed for research institutions, universities, SMEs, large enterprises, and other legal entities capable of conducting research and innovation activities.

Consortium

The funding encourages multi-partner consortia, emphasizing collaboration across different disciplines and institutions.

Funding Amount

Each project can receive up to €10 million, with a total budget of €29 million allocated for approximately 3 projects.

Countries

The funding is relevant for EU Member States and Associated Countries, as well as non-EU/non-Associated Countries with specific provisions for participation in Horizon Europe projects.

Industry

This funding targets the integration of AI and laboratory automation within the Horizon Europe framework, specifically under the AI in Science initiative.

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Description II
Expected Outcome:Development of closed-loop scientific experimentation systems that integrate automation with AI-driven, trustworthy decision-making processes in existing laboratory environments;Accelerated scientific discovery with increased efficiency and reproducibility;Improved scientific productivity;Advancement of laboratory automation, including development of best practices, challenges, and opportunities for accelerating R&D; andPrototype functional demonstrators that showcase the integration of automation with AI-driven decision-making, enabling the development of closed-loop scientific experimentation systems. Scope:This topic addresses the development of safe and trustworthy closed loop scientific experimentation systems through the integration of laboratory automation with AI-driven decision-making processes and robust data infrastructures. Funded projects will help scientific labs with an already advanced level of automation and digitalisation to design, develop, and test ...

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