Humanity AI (Forthcoming Open Call)

Developing managed aquifer recharge techniques (MAR) in a rural context is sponsored by European Commission — Horizon Europe. Expected Outcome: Project results are expected to contribute to all of the following expected outcomes: farmers have access to water supply from managed aquifer recharge systems and to appropriate business models to cope with longer and more intense periods of water scarcity due to climate change, while preserving the good status of ground water bodies; water ecosystems are healthier and more resilient to climate change, and water related ecosystem services are protected and strengthened, while water resilience of farming systems is increased; policy makers are provided with improved insights on mechanisms and instruments to improve the water resilience of the agricultural sector to cope with climate change effects. Scope: Droughts in the EU are increasing in frequency, magnitude and impact, and the affected area is expanding. Water storage systems can limit abstractions from surface waters and groundwater reducing the environmental footprint of agriculture and food systems, and bring the demand and supply of water better in balance, strengthening the resilience of EU agriculture. Proposals should: extend, improve and customize managed aquifer recharge (MAR) techniques at farm, basin and catchment level, covering most representative EU agricultural contexts in view of climate change; develop a methodology to help assessing the most suitable location or situations to implement these MAR techniques and validate with a representative sample of case-study regions, taking into account for the differential impact of climate change; develop a user-friendly monitoring, reporting and verification system (MRV) to follow the impact on ground water quality and quantity, as well as associated water ecosystems and dependent terrestrial ecosystems; evaluate the potential impact and sustainability of managed aquifer recharge techniques in rural areas, including on the groundwater ecosystems, associated water ecosystems and dependent terrestrial ecosystems, and drinking water from a multi-objective approach, and its integration with evidence-based engineered and Nature-based Solutions to reduce runoff, soil erosion and improve landscape climatic resilience; calculate the cost-benefits of MAR techniques and propose different business models for the compensation or remuneration of individual farmers or land managers (payments schemes, nature, carbon or water credits, …) for hosting MAR initiatives; demonstrate the feasibility of these business models at local level (catchment, river basin, ...) by at least 2 case studies in different pedoclimatic zones and evaluate the possible barriers for adoption by farmers or land managers; provide a framework of governance models that could fit the different local socio-economic, regulatory and pedo-climatic conditions. The actions funded under this topic are relevant to the EU policies related to the EU Vision for Agriculture and Food, as well as to the European Water Resilience Strategy and the EU Climate Adaptation Strategy. Proposals must implement the multi-actor approach and ensure adequate involvement of relevant stakeholders, including farmers, land managers, water governance bodies and local authorities. Proposals are encouraged to build on the results of relevant projects funded under Horizon 2020 and Horizon Europe and ensure collaboration with relevant ongoing and forthcoming projects from the Mission Soil and the Mission Ocean & Waters. Proposals should follow the Guidance document on managed aquifer recharge techniques of the CIS Working Group on Groundwater [1] . Technology Readiness Level - Technology readiness level expected from completed projects Activities are expected to achieve TRL 4-5 by the end of the project – see General Annex B. [1] Common implementation strategy for the water framework directive and the floods directive: https://op.europa.eu/en/publication-detail/-/publication/e827bbe4-fe33-11ef-b7db-01aa75ed71a1/language-en Programme areas: Horizon Europe (HORIZON), Global Challenges and European Industrial Competitiveness, Food, Bioeconomy Natural Resources, Agriculture and Environment, Agriculture, Forestry and Rural Areas Keywords: Business analysis, Business governance, Business models, Catchment scale planning, Environmental engineering and geotechnics, Environmental impact assessment, Human impacts and other stressors, Hydrology (Water science), Natural resources and environmental economics, Nature-based solutions, Water management, Water recycling and re-use, Water technology, MAR, MRV, business model, climate adaptation, drought, groundwater, impact analysis, managed aquifer recharge, monitoring, reporting and verification system, multi-actor approach, nature-based solutions, sustainable agriculture, water ecosystem, water management, water resilience, water storage

Advanced Digital Skills for AI Uptake in Health is sponsored by European Commission — Digital Europe Programme. Expected Outcome: Deliverables: Initiatives implemented for the target audience to collect knowledge on learning needs in the area of AI uptake in health. Training programmes in the area of advanced digital skills for AI uptake in health, designed jointly by higher education institutions, VET providers, research organisations, businesses and other stakeholders in digital health, in collaboration with the network of AI-powered advanced screening centres. Training catalogue with detailed course planning and timetable, regularly updated. Final analysis of the completed training and the achievement level reached in improved skills. A landing page integrated into the Digital Skills and Jobs Platform, showcasing existing and forthcoming education and training initiatives and promoting training offers to the relevant audience. Objective: The academic offer in the area of advanced digital technologies in the EU is still lagging behind other regions of the world, especially when compared to the United Kingdom or the United States [1] even though the number of both bachelor’s and master’s programmes in the EU has increased through the years. Furthermore, apart from delivering excellent programmes in specific digital technologies, there is also a growing demand for interdisciplinary programmes to equip sector specialists with the digital skills to deploy and use advanced digital technologies. The actions under this topic aim at tackling the lack of academic training offer in advanced digital skills in key digital areas, while triggering a new way of delivering education programmes and training, building partnerships between education and training providers, businesses and research across the EU, and supporting the digital skills necessary for the deployment of digital technologies in strategic sectors. 1 This represents an increase of 8% in the number of bachelor programmes and an increase of 14% in the number of master programmes in the area of advanced digital skills. The dataset by the Joint Research Centre on the ‘Academic offer of advanced digital technologies 2022-2023’ is available here: JRC Data Catalogue - Dataset - European Commission Scope: This topic aims to expand the offer of education and training in Artificial Intelligence in health jointly designed between higher education and training institutions, research organisations and industry. The content must reflect the latest policy developments, notably the Apply AI Strategy [1] and the European Health Data Space [2] . It should cover developments in and application of AI and related digital health technologies. The target audience is healthcare professionals, as well as computer and data scientists, programmers, and software developers working in the healthcare sector. Trainings must reflect the learning needs of the target audience and will vary in depth and technical complexity to accommodate different levels of expertise and learning preferences. To this end, the proposed project(s) should design and deliver the trainings in cooperation with the Apply AI Strategy flagship “European network of AI-powered advanced screening centres” [3]. The training courses should be made available to members of the “European network of AI-powered advanced screening centres” at least quarterly. The training sessions and material should be available in English and other EU languages, considering the needs of the target audience that need to be established. The training catalogue and content should be adapted regularly, according to target audience feedback. Whenever applicable, the projects should foster the use of the HealthData@EU infrastructure and other European health data infrastructures (Genomic Data Infrastructure, Cancer Image Europe, the European Virtual Human Twins advanced platform, ICU data space), explore synergies and build on relevant education and training activities developed and provided in the context of those initiatives, as well as in the relevant projects funded by E Programme areas: DIGITAL-1 Keywords: Artificial intelligence, Artificial intelligence, intelligent systems, multi agent systems, Computer sciences - Operating systems (software development only), Continuing professional training, Curriculum design and development, Design of innovative master related to European Innovation potential, Digital Services and Platforms, Education, Education and Training, Health and Ecosystem Services, Health data, Health sciences, IT skills and competence, Identification of skills needs, Inclusive Education, Integration and upscaling of digital technologies and media in education, Interoperability, Learning outcomes, Master's or equivalent, New employement profiles and identification of skills, Personal development, Qualification, Teaching materials, Technological innovation, Training, Advanced Digital Skills, Cross-Sectoral Collaboration, Digital Health Education, European Health Data Space and infrastructure, European Health Initiatives, Health Workforce Development, Health care professionals, Health care students, High level expertise for healthcare, STEP-Digital/deep tech

Automated Scientific Discovery is the most ambitious strand of RAISE, the European Commission's Resource for AI Science in Europe pilot - a roughly EUR 100 million coordinated package that press coverage has framed as an attempt to build a CERN for AI. The scientific target here is AI systems that do not merely assist researchers but close the loop: generating hypotheses, designing experiments, interpreting results and iterating with limited human intervention. That places the topic at the intersection of large language model reasoning, autonomous laboratories, and the domain-specific modelling needed to make machine-generated hypotheses worth testing, and successful consortia will almost certainly need to combine AI methods groups with experimental facilities rather than proposing either alone. The indicative budget is EUR 30 million across an expected three projects, which implies unusually large individual grants of roughly EUR 10 million and correspondingly large, multi-disciplinary consortia. The deadline is 2 February 2027. A companion topic, HORIZON-RAISE-2027-01-02, applies the same automated-discovery agenda to food research with a EUR 3 million budget and a single expected project, and shares the same deadline - teams whose application domain is food systems should target that narrower topic rather than competing in the general call. The broader RAISE portfolio also includes thematic networks of excellence and MSCA-model doctoral networks for AI in science, so groups whose strength is training rather than discovery infrastructure have alternative routes within the same initiative. Because these 2026-2027 calls are explicitly pilots for the Commission's forthcoming AI in Science strategy, proposals that articulate how their outputs would feed a permanent European AI-for-science resource are likely to read well against the impact criteria.