European Startup and Scaleup Hubs pilot

Expected Outcome: Projects are expected to contribute to all the following expected outcomes: Effective and innovative methods for gathering, sharing and using large data sets in energy applications for the purpose of training AI models while ensuring privacy and security. Advanced and - wherever possible - open-source AI foundation models to support the digitalisation of the energy system, through improved grid observability, forecasting of supply and demand, advanced storage and renewables integration, demand side flexibility and energy efficiency. Enhanced cooperation, knowledge sharing and interoperability among energy system actors for secure and seamless data exchange. Advanced methodologies for AI model development ensuring that the results are FAIR (Findable, Accessible, Interoperable, Reusable) beyond the project ending, open source and accommodating for technology evolution. Scope: The quality of AI models depends strongly on the amount, quality, and representativeness of the data used for their training. Projects are expected to focus on developing, training and testing AI foundation models, using extensive data sets to accelerate the energy transition in key focus…

Expected Outcome: Project results are expected to contribute to some or all of the following expected outcomes: Improved skills, tools and training curricula for Police Authorities in Europe and Civil Society Organisations (or Non-Governmental Organisations) to work with at-risk groups to prevent persons from going missing. Those improved skills, tools and training curricula are to take into account European multicultural dimension, as well as legal and ethical rules of operation; Enhanced investigation tools and methodologies for Police Authorities in Europe to tackle cold cases in the context of missing persons, based on modern (forensic) technologies and criminology; Modern training curricula for Police Authorities, their improved cross-border cooperation and enhanced tools and methodologies to tackle new cases of missing persons; Enriched European common approaches applied by Police Authorities in Europe to fight the issue of missing persons relying on the synergy of technology, the latest socio-psychological knowledge learned from cases, as well as field experience of Police Authorities and entities dealing with victims, while fully respecting fundamental rights such as…

Expected Outcome: Project results are expected to contribute to all of the following expected outcomes: Police Authorities in Europe are empowered with modern, accessible and validated tools, methodologies and training curricula to anticipate and cope with the misuse of new and emerging technologies for criminal purposes, with the aim to facilitate prevention, detection, efficient data access and investigation of criminal offences in a lawful manner and with full respect of fundamental rights, including the right to protection of personal data and to privacy; Reinforced interdisciplinary collaboration at the European level through the establishment of partnerships among technologists, policymakers and Police Authorities, resulting in a holistic understanding of the challenges posed by emerging technologies and in sharing of best practices; Clear guidelines and frameworks are created, including on procedures and rules, that ensure lawful access to data, balancing the needs of security with respect for privacy and that foster a European approach to the related challenges for the police and the judiciary. Scope: New and emerging technologies (e.g., new communication technologies,…

Expected Outcome: One or more of the following should be covered: Implementation of guidelines, standardised processes, or manuals – in the EU or multiple EU MS – concerning the most challenging issues, supporting specific stakeholders and sectors addressed by cybersecurity legislation. Develop and implement tools, raise awareness and encourage and facilitate industry uptake, with a focus on SMEs, of conformity assessments of essential cybersecurity requirements for products with digital elements (hardware and software) under the CRA. Support for mechanisms reducing the administrative burden for entities, like single entry point for incident notification. Establish secure communication channels allowing for cooperation and information sharing initiatives. Support the organisation of regular meetings/workshops to identify good practices within specific sectors or emerging areas and facilitate collaborative efforts between different sectors. Support the development of training courses, on the basis of the ECSF and exercises that promote capacity building and internal awareness. Contribution to CR standardisation: Training materials and training actions on cybersecurity certification…

Expected Outcome: Support the adoption of market-ready innovative AI-powered cybersecurity solutions, including solutions developed in the framework of EU-supported research and innovation projects. Provide and deploy up to date AI-powered tools and services to organisations (in particular SMEs) to prepare, protect and respond to cybersecurity threats. Integrate AI technologies into cybersecurity processes to improve the security of ICT solutions, including providing innovative approaches to training employees to use AI solutions for cybersecurity. Deployment of cybersecure tools and technologies relying on trustworthy AI; AI driven cybersecurity tools; Integration of tools to protect and secure AI solutions. Objective: To support the market uptake and dissemination of innovative AI-powered cybersecurity solutions (notably in SMEs, possibly using results stemming from Horizon Europe projects or similar) and improve knowledge and auditing of cybersecurity preparedness. SMEs often lack the resources to assess cyber risks, develop cybersecurity strategies and implement solutions, leaving them vulnerable to cyberattacks. The resilience of organisations that fall into this category is…

Expected Outcome: Proposals are expected to contribute to all of the following expected outcomes: policy and decision makers at relevant levels are better equipped to incorporate educational, cultural, societal and behavioural insights related to biodiversity – such as business dependencies, vulnerabilities and systemic risks – into future policy development, including through participatory and co-designed approaches; institutional, business, financial and economic actors have better awareness on the systemic effects of their interactions and interdependencies with ecosystems, including international trade, across value chains; the understanding and mapping of cross-actor and cross-sectoral relationships and their associated knowledge production and decision-making pathways are improved; transdisciplinary research communities from natural and social sciences and humanities (SSH), as well as cultural and creative sectors, among others, collaborate to improve understanding on the indirect drivers [1] behind biodiversity-harming practices, identify leverage points and test evidence-based interventions – including in relation to governance, incentives, narratives, norms and power…

Expected Outcome: Project results are expected to contribute to the following outcomes: For supported doctoral candidates New research and transferable skills and competences, leading to improved employability and career prospects within and outside academia; New knowledge allowing the conversion of ideas into products and services, where relevant; Enhanced networking and communication capacities with scientific peers, as well as with the general public that will increase and broaden the research and innovation impact. For participating organisations Improved quality, relevance and sustainability of doctoral training programmes and supervision arrangements; Enhanced cooperation and transfer of knowledge between sectors and disciplines; Increased integration of training and research activities between participating organisations; Boosted R&I capacity; Increased internationalisation and attractiveness; Regular feedback of research results into teaching and education at participating organisations. Scope: MSCA Doctoral Networks will implement doctoral programmes, by partnerships of universities, research institutions and research infrastructures, businesses including SMEs, and other…

Expected Outcome: This action builds on the MSCA Doctoral Networks 2026 call (HORIZON-MSCA-DN-2026). The project results are expected to contribute to the following outcomes: For supported doctoral candidates: New research and transferable skills and competences in the application of AI in science, leading to improved employability and career prospects within and outside academia; New knowledge allowing the conversion of ideas into products and services, where relevant; Enhanced networking and communication capacities with scientific peers, as well as with the general public that will increase and broaden the research and innovation impact. For participating organisations: Improved quality, relevance and sustainability of doctoral training programmes and supervision arrangements; Enhanced cooperation and transfer of knowledge between sectors and disciplines; Increased integration of training and research activities between participating organisations; Boosted R&I capacity and uptake of AI in science; Increased internationalisation and attractiveness; Regular feedback of research results into teaching and education at participating organisations. Scope: Successful RAISE Doctoral…

Scope: The EIC Accelerator supports companies (principally SMEs, including start-ups) to scale up high impact innovations with the potential to create new markets or disrupt existing ones. The EIC Accelerator provides a unique combination of grant and investment funding and Business Acceleration Services (see Section VII of EIC Work Programme 2026). The EIC Accelerator focuses in particular on innovations building on scientific discovery or technological breakthroughs (‘deep tech’) and where significant funding is needed over a long timeframe before returns can be generated (‘patient capital’). Such innovations often struggle to attract financing because the risks and time period involved are too high. Funding and support from the EIC Accelerator is designed to enable such innovators to attract the full investment amounts needed for scale up in a shorter timeframe. The EIC Accelerator supports the later stages of technology development as well as scale up. The technology component of your innovation must therefore have been tested and validated in a laboratory and other relevant environment (e.g., at least Technology Readiness Level 5 completed). The EIC Accelerator looks to…

Expected Outcome: The successful proposal is expected to further contribute to the expected outcomes specified in topic HORIZON-CL6-2024-GOVERNANCE-02-01: European Partnership of Agriculture of Data, for continuation of the activities in line with already agreed outcomes. Scope: The objective of this action is to continue to provide support to the European partnership of Agriculture of Data identified in the Horizon Europe Strategic Plan 2021-2024 and first implemented under the topic HORIZON-CL6-2024-GOVERNANCE-02-01: European Partnership of Agriculture of Data, and in particular to fund additional activities (which may also be undertaken by additional partners) in view of its intended scope and duration, and in accordance with Article 24(2) of the Horizon Europe Regulation. The consortium which applied to and received funding under HORIZON-CL6-2024-GOVERNANCE-02-01: European Partnership of Agriculture of Data is uniquely placed to submit a proposal to continue the envisioned partnership. Not only did this consortium submit the proposal leading to the identification of the partnership in the Horizon Europe strategic planning 2021-2024, it has also been implementing the…