Automated Scientific Discovery (RAISE pilot) (RIA)
Forthcoming
Status as published by the data source.
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; and
• Prototype 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 the intelligence layer that enables scientific instrumentation to semi- or fully autonomously plan, run, and analyse experiments, ideally in coordination/network with other labs and without requiring a complete redesign of existing laboratory outfitting.
Proposals will incorporate comprehensive data management systems capable of handling 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 to facilitate data sharing and collaboration across labs, while ensuring data security and privacy.
Systems could incorporate AI-driven resource optimisation modules, actively minimising energy, reagent, and material consumption during automated experimentation cycles. Systems should incorporate 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 analyse experiments in a closed-loop fashion, incorporating human oversight and interaction to ensure accuracy, safety, and ethical compliance.
Possible research targets include (non-exhaustively):
• 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 of computer/AI scientists and domain scientists.
While the scope of this call prioritises software development, it does not exclude the justified purchase of complementary equipment necessary to implement the research targets of the project.
An initial focus on materials science is put forward (Cluster 4). Impact areas of automated experimentation in this field could include (non-exhaustively) drug discovery, battery technologies, photovoltaics, carbon capture/storage, water purification, soil remediation, environmentally friendly fertilizers, development of alternative protein sources in food production, sustainable fabrics/dyes.
The thematic focus of this topic 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, for example with HORIZON-CL4-INDUSTRY-2025-01-DIGITAL-61.
- Status
- Forthcoming
- Deadline
- (time not stated)
- Opens
- Published
- Total budget
- €29,000,000
- Grant range
- €10,000,000 – €10,000,000
- Country
- European Union (EU-wide)
- Programme
- Horizon Europe (HORIZON)
- Official page
- Open at the source portal
Other calls under Horizon Europe (HORIZON)
- PV based electrification of the economy: Designing & optimising PV systems supporting industrial electrification and promoting participation in electricity markets (EUPI-PV Partnership)
- Advanced TSO control rooms to enhance grid observability, stability and resilience
- Advanced Distribution Management Systems (ADSM) for more efficient and flexible distribution grids
- Community of practice - Data-Driven Decision-Making in Energy
- Industrial processes and equipment for innovative, reliable and scalable tandem technologies (EUPI-PV Partnership)
- Integrated Approaches for Retrofitting Infrastructures with Innovative Energy Storage Technologies
- Demonstration of hydropower technologies for efficient and forward-looking refurbishment of existing hydropower plants
- Delivery of industrial CCUS clusters – Societal Readiness pilot
All calls under this programme
Similar opportunities
- Automated Scientific Discovery – Food (RAISE pilot)
- RAISE Doctoral Networks for AI in Science (RAISE pilot)
- Apply AI: Challenge-Driven AI Innovation Booster in Apply AI prioritised sectors (RIA) (Partnership in AI, Data and Robotics)
- New approaches for Human/AI collaboration for the workforce of the future (RIA) (Made in Europe and AI, Data and Robotics partnerships)
- Apply AI: AI-Driven Robotics for Industry: Enabling System Integration and Adoption (IA) (Partnership in AI, Data and Robotics)
- Collaborative intelligence – combining the best of machine and human (AI Data and Robotics Partnership) (RIA)
Where this came from
- Source document
- https://ec.europa.eu/info/funding-tenders/opportunities/data/topicDetails/horizon-raise-2027-01-01.json
- Document fingerprint
9a46f382848d3df0(SHA-256, first 16 hex characters)- Retrieved
- First recorded here
What has changed
- url first recorded as https://ec.europa.eu/info/funding-tenders/opportunities/portal/screen/opportunities/topic-details/horizon-raise-2027-01-01 on
- currency first recorded as EUR on
- amount_max first recorded as 10000000.00 on
- amount_min first recorded as 10000000.00 on
- budget_total first recorded as 29000000.00 on
- deadline first recorded as 2027-02-02 on
- opens_on first recorded as 2026-09-22 on
- published_on first recorded as 2025-12-12 on
- status_basis first recorded as source_status on
- status first recorded as forthcoming on
- title first recorded as Automated Scientific Discovery (RAISE pilot) (RIA) on
Data source
© European Union, 2026. Source: EU Funding & Tenders Portal. Reused under Commission Decision 2011/833/EU — CC BY 4.0.
Retrieved from the source on .
The source last updated this document on Mon, 02 Mar 2026 09:33:44 GMT.
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