Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Aware Systems for Smart Interactive muSeums and arT (ASSIST)

Framework: Horizon Europe — Innovative Europe
Programme: The European Innovation Council (EIC)
Theme: other EIC
Destination: Other destinations
Action type: Coordination and support actions
Countries involved: Spain
Call: EIC Booster grant for EIC Pathfinder and EIC Transition grants (HORIZON-EIC-2024-BOOSTER-IBA-01, 2024)
Start date: 2025-02-01
End date: 2025-06-30
Duration (months): 5.0
Total project cost (EUR): 71428.57
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Artificial Intelligence (AI) is transforming the world we live in. In the last decade, deep learning algorithms have enabled AI systems to perform tasks like speech and image recognition, matching or surpassing human capabilities. However, AI will not be enough to deliver human-level intelligence without a sort of “artificial awareness” that could provide the ability to focus its computational resources and intelligently control them to interact with people in a socially competent manner. This project streams from the EIC Pathfinder project ASTOUND (GA 101071191), which is currently developing an Integrative Approach for Awareness Engineering to establish consciousness in machines. The requested Booster Grant will support the commercial validation of ASTOUND's new contextually aware chatbots in the tourism sector, identified as a potential initial target market. In fact, exploiting novel contextually aware chatbots in the tourism sector could offer immediate and impactful benefits, as tourists often require real-time, context-specific information and assistance, which these advanced chatbots can effectively provide. Additionally, the chatbots could pave the way for the “future museum”, a museum that could become like a thematic park in which visitors could really appreciate the value of on-site visits vs. virtual visits by, for example, generating an emotional link with the original piece of art. To explore the pathways to commercialise this breakthrough innovation, the project has set the following objectives: 1. Conduct market analysis and product-market fit assessment to validate the commercial viability of deploying the novel contextually aware chatbot in the tourism sector; and 2. Fine-tune a demo of the AST-based chatbot using datasets specifically tailored for the tourism sector.

Keywords: artificial intelligence,awareness,consciousness,conversational agent,chatbot,tourism,museum,artificial intelligence,neuroscience,cognitive science,
Designer Condensates for Regulation of Catalytic Processes (CORE)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Biotechnology and Biosystems E ngineering
Panel description: Biotechnology using all organisms , biotechnology for environment  and food applications, applied plant and animal sciences , bioengineering and synthetic biology , biomass and biofuels , biohazards
Countries involved: Israel
Call: ERC STARTING GRANTS (ERC-2024-STG, 2024)
Start date: 2024-10-01
End date: 2029-09-30
Duration (months): 60.0
Total project cost (EUR): 1498750.0
EU funding (EUR): 1498750.0
Participants: 1
Project status: SIGNED

Living cells have evolved to provide subcellular microenvironments that accommodate and control specific (bio)catalytic processes. These compartments include membrane-bound and membraneless organelles, or biomolecular condensates. New breakthroughs in studying and characterizing cellular biomolecular condensates have facilitated researchers to design synthetic condensates that are formed by liquid-liquid phase separation of engineered proteins, polypeptides, peptides, or nucleic acids. Yet, a precise regulation of designed condensates’ properties and their utilization for nanobiotechnological applications remains a major challenge. I propose to utilize my expertise in peptide design to develop libraries of synthetic condensates with systematically tunable chemical composition using minimalistic LLPS-promoting peptide building blocks. I will analyze how the chemical composition of condensates affect their physical and material properties and harness this knowledge to regulate organic reactions and drug synthesis in engineered microenvironments and develop condensates with emergent collective catalytic capacity. The proposed research will elucidate how the chemical composition, physical, and material properties of designed condensates affect reaction rate, conversion, and condensate reactivity. The designed condensates will go beyond the state of the art of synthetic nano- and microreactors and provide the next generation of reaction regulation for sustainable drug synthesis in organic solvent-free, aqueous environment. These findings will pave the way to establish novel design principles for the fabrication of synthetic condensates from peptide building blocks with both ordered and disordered motifs, leading to precise controlling, and balancing of these motifs to regulate reactivity effectively. I expect that this research will promote the LLPS, self-assembly, and nanobiotechnology communities for the development of condensates for emerging nanotechnologies.

Keywords: liquid liquid phase separation biomolecular condensates designed condensates coacervates peptides self assembly reactions compartmentalization
Biomaterials Design through Machine Learning for Sex- and Disease-Specific Bone Regeneration (SeDiBone)

Framework: Horizon Europe — Excellent Science
Programme: Marie Skłodowska-Curie Actions (MSCA)
Theme: Marie Skłodowska-Curie
Destination: Postdoctoral Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Life Sciences
Countries involved: Netherlands
Call: MSCA Postdoctoral Fellowships 2023 (HORIZON-MSCA-2023-PF-01, 2023)
Start date: 2025-06-01
End date: 2027-05-31
Duration (months): 24.0
Total project cost (EUR): 203464.32
EU funding (EUR): 203464.32
Participants: 1
Project status: SIGNED

Osteoporosis, a widespread disease that causes bone fragility, currently afflicts over 32 million Europeans, with rapidly increasing prevalence expected due to population aging. The costs of therapies for osteoporotic fragility fractures total more than €50 billion per year in the EU. Postmenopausal females are at especially increased risk for osteoporosis, and the regenerative capacity of healthy bone also differs between the biological sexes. Although biomaterials have been developed to aid bone regeneration after injury, the influence of biological sex and osteoporotic disease have not been taken into account for such biomaterials design. Excitingly, the advent of machine learning (ML) offers the potential to unravel the effects of sex and osteoporotic disease on biomaterials’ bone regenerative capacity, and to apply these insights to design biomaterials optimized to these characteristics. Therefore, the SeDiBone project will – for the first time – exploit ML to elucidate the influence of sex and osteoporotic disease on bone regeneration, and to translate these insights towards design of an entirely new class of biomaterials with sex and osteoporotic specificity. By enabling automated localization of tissue defect sites and detailed tissue, cell, and interface identification, SeDiBone will deliver an Analysis Tool that efficiently and reproducibly quantifies bone regeneration outcomes in male or female and healthy or osteoporotic preclinical animal models (Aim 1). These in-depth insights will then serve as inputs for a Design Tool to determine the biomaterials designs correlating to optimal regenerative success based on sex and osteoporosis, with validation through ex vivo demonstration (Aim 2). SeDiBone will thus crucially synergize and advance efforts to design a new generation of patient-specific biomaterials, and accordingly inform therapeutic solutions for regeneration of bone tissue in the unexplored areas of sex- and disease-based specificity.

Keywords: bone,regenerative medicine,osteoporosis,histology,histomorphometry,in vivo,orthopedic,craniofacial,dental,surgery
MAINSTREAMING A UNIFYING NARRATIVE FOR SUSTAINABLE AND INCLUSIVE WELLBEING (WISE Narrative)

Framework: Horizon Europe — Widening Participation and Strengthening the European Research Area
Programme: Widening participation and spreading excellence
Theme: Improved access to Excellence
Destination: Improved access to Excellence
Action type: Research and Innovation actions
Countries involved: Netherlands,Portugal
Call: Hop on Facility (HORIZON-WIDERA-2023-ACCESS-06, 2023)
Duration (months): 24.0
Total project cost (EUR): 382418.75
EU funding (EUR): 382418.75
Participants: 2
Project status: CLOSED

The WISE HORIZONS (WH) project aims to support a societal transformation towards wellbeing, inclusion, and sustainability (WISE) by developing a coherent and integrative narrative as an alternative to a historical economic growth-based narrative. Building on WH’s theoretical framework, WISE NARRATIVE (WN) seeks to fill a gap in understanding the co-production and mainstreaming of both growth-based and alternative narratives allowing to better inform policy and society about the choices that will shape the future up to 2050. By engaging narrative diffusion agents (e.g., journalists, influencers, civil society leaders) and their audiences (i.e., policymakers, technology and market innovators, citizens), WN will accelerate the creation and dissemination of a WISE narrative. The project’s objectives include: 1) analysing the historical growth-centric narrative and its metrics through a review of news media articles and political manifestos; 2) comparing alternative narratives, such as degrowth and circular economy, in documents from global regions; 3) experimenting with WISE narrative discourses and framings via vignette experiments with narrative diffusion agents and citizens; and 4) co-creating the final narrative through stakeholder workshops and focus groups. Employing innovative methods -machine-learning topic modeling, survey experiments, and participatory techniques - WN will provide new data on narrative dynamics and foster the integration of diverse perspectives across the Global North and South. This will catalyse a shift towards a sustainable, inclusive policy framework, complementing WH’s institutional approach with bottom-up and inclusive engagement, improving research excellence in the widening country through a novel methodology approach, and filling a gap in Portugal's participation in projects funded under this topic.

Keywords: wellbeing,inclusion,sustainability,equality,narratives,topic modelling,vignette survey experiments,co creation
A Foundation Model for Next-Generation Generalizable AI in Neuro-Radiology (AI-Next)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Prevention,  Diagnosis and T reatment of Human Diseases
Panel description: Medical technologies  and tools for prevention, diagnosis and treatment of human diseases, therapeutic approaches and interventions , pharmacology, preventative  medicine, epidemiology and public health , digital medicine
Countries involved: Germany
Call: ERC CONSOLIDATOR GRANTS (ERC-2024-COG, 2024)
Start date: 2025-06-01
End date: 2030-05-31
Duration (months): 60.0
Total project cost (EUR): 2533448.75
EU funding (EUR): 2533448.75
Participants: 2
Project status: SIGNED

Medical artificial intelligence (AI) holds immense promise for transforming radiology by introducing advanced diagnostic capabilities. Yet, traditional AI models face challenges like extensive data annotation needs and are task-specific with limited generalizability to different scenarios. This problem of robust and label-efficient generalization continues to be a key translational challenge for medical AI models and has prevented their broad uptake in real world healthcare settings. AI-Next will build on the recent advent of foundation models, providing a unique opportunity to rethink the development of medical AI and overcome the challenges of traditional AI models. At the core of AI-Next stands the development of a state-of-the-art visual foundation model (VFM) that learns generalizable representations from unlabelled radiology scans and provides a basis for label-efficient model adaptation in several applications. The VFM will focus on neuro-radiology and be trained with data at unprecedented scale including >200,000 brain computed tomography and magnetic resonance imaging scans from population-based and disease specific cohorts, leveraging self-supervised learning. The VFM will be adapted with a limited set of explicit labels to a range of tasks with clinical significance. This includes the screening and triage of scans for emergency findings, longitudinal disease activity assessment, risk prediction of dementia, forecasting of disease evolution and finally automated radiology reporting. Moreover, the VFM will be employed for image processing tasks, including generating super-resolution images to enhance diagnostic capabilities. Overall, AI-Next will represent a crucial step towards more generalisable, accurate and label-efficient AI in neuro-radiology, offering significant potential for improving diagnostics, clinical decision-making as well as patient outcomes, and its open-source innovations will serve as a blueprint for the broader field of radiology.

Keywords: radiology neuroradiology neuroimaging artificial intelligence foundation models
Multimodal Engagement and sustainable Lifestyle Interventions Optimizing breast cancer Risk reduction supported by Artificial intelligence (MELIORA)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Mission
Theme: Cancer
Destination: Cancer
Action type: Research and Innovation actions
Countries involved: Greece,Sweden,Spain,Lithuania,Poland,Belgium,Germany
Call: Enhance primary cancer prevention through sustainable behavioural change (HORIZON-MISS-2023-CANCER-01, 2023)
Start date: 2024-01-01
End date: 2027-12-31
Duration (months): 48.0
Total project cost (EUR): 5858985.0
EU funding (EUR): 5857735.0
Participants: 16
Project status: SIGNED

MELIORA Consortium will jointly work with local actors at different levels for the realization of eight (8) in total tailor-made lifestyle intervention and behavioural modification studies, including Artificial intelligence and digital tools, to promote sustainable behavioural changes among three target populations: i) healthy women at risk of developing breast cancer, ii) breast cancer patients and iii) breast cancer survivors. The studies will take place across 4 different European countries (Greece, Sweden, Spain and Lithuania) and 6 piloting centres targeting 2000 women in urban and rural areas including participants throughout the socioeconomic spectrum. Primary health care centres, hospitals or patients’/survivors’ organisations will be used as entry points to the community. The goal of the MELIORA Virtual Coach interventions is to evaluate its effectiveness, through assessing the effect of multiple individual and contextual factors to the uptake and sustainability of behavioural changes. At the same time, identification of specific bottlenecks and barriers that prevent the uptake of sustainable behavioural change will support the development of approaches on how to best reach and involve disadvantaged socio-economic population groups, vulnerable groups, and people living in rural areas, and will provide best practices for behavioural intervention uptake and scale-up. Regular monitoring will be ongoing during the implementation to allow corrective actions and ensure effective adaptation and uptake. Based on the study outcomes, the health economic evaluation and budget impact analysis, and data deriving from the scalability assessment, national and European stakeholders will be invited to evaluate, through workshops, the potential for adoption of the MELIORA Virtual Coach Interventions in other regions or countries in Europe. This action is part of the Cancer Mission cluster of projects on “Prevention & early detection (behavioural change).

Keywords: breast cancer,cancer prevention,sustainable intervention,nutrition,exercise,public health,cancer risk factors,health communication,digital health,health technologies,artificial intelligence
Robyn is the first holistic anonymous 3D Avatar and AI coach to provide clinically validated CBT-based support to combat mental health, empower people and provide them with exceptional longevity. (Robyn)

Framework: Horizon Europe — Innovative Europe
Programme: The European Innovation Council (EIC)
Theme: EIC Accelerator
Destination: Other destinations
Action type: EIC actions
Countries involved: Netherlands
Call: EIC Accelerator 2024 - Short application (HORIZON-EIC-2024-ACCELERATOR-01, 2024)
Duration (months): 18.0
Total project cost (EUR): 1199660.0
EU funding (EUR): 1199660.0
Participants: 1
Project status: SIGNED

This EIC project will facilitate the development of Robyn, a clinically validated AI coach offering direct first-line support. Robyn is an app with realistic conversational 3D avatars and a holistic AI coach utilizing advanced proprietary algorithms, and addresses the problem of extremely high levels of stress among GenZs and the social gap that emerged in the aftermath of the COVID-19 pandemic. It does this by providing easy, direct and anonymous access to clinically validated solutions designed to combat mental health issues. Robyn assists GenZs in managing stress and anxiety, encourages them to voice their concerns, and helps them develop effective behaviours that have a lasting impact. Once fully operational across the EU, Robyn is projected to reduce stress-related issues by 30%, potentially saving the EU over €6B per year in lost productivity and healthcare costs.

Keywords: 3d human like avatar,anonymous and direct cbt based mental health support support,empower people,exceptional longivity
INDIVIDUALISED CARE FROM EARLY RISK OF CARDIOVASCULAR DISEASE TO ESTABLISHED HEART FAILURE (iCARE4CVD)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Health
Theme: Public-private partnerships
Destination: Innovative Health Initiative
Action type: Research and Innovation actions
Partnership: IHI (JU-JTI)
Countries involved: Switzerland,Germany,Netherlands,Ireland,France,Denmark,United States,Sweden,United Kingdom,Belgium,Italy,Austria,Spain,Finland
Call: Cardiovascular diseases - improved prediction, prevention, diagnosis, and monitoring (HORIZON-JU-IHI-2022-02-two-stage, 2022)
Start date: 2023-10-01
End date: 2028-03-31
Duration (months): 54.0
Total project cost (EUR): 21094692.02
EU funding (EUR): 9942458.81
Participants: 43
Project status: SIGNED

The burden of cardiovascular disease (CVD) on society is huge with >85 million people affected in Europe. The overall prevalence continues to grow due to unhealthy lifestyles and population aging. Heart failure (HF) is the final common pathway of all CVD and has a 5 year mortality rate of 20-50% despite significant advances in therapy. iCARE4CVD aims to address this burden by contributing to three essential steps to improve the current care pathways, covering all stages from early risk to established HF: 1) early diagnosis to identify patients at risk of CVD and divide them into clinically meaningful subgroups; 2) risk stratification for these subgroups to define the urgency for intervention; and 3) prediction of treatment response for each subgroup. This will be achieved by the following steps: clinical partners will provide a large set of cohorts including >1,000,000 patients with a wide range of biomarkers (e.g. digital, blood, imaging). Anonymous access to data will be enabled by using a blockchain-supported federated database. Artificial intelligence-based modeling also considering patient relevant factors will assess changes in risk and stratify patients according to their individual responses to therapy. Results will then be prospectively validated in new and ongoing large cohorts and a pilot trial to test the prediction of treatment response by using multiple biomarkers going beyond current risk prediction (such as SCORE) towards individualized therapy. Results will be used to provide novel decision tools for each step targeting newly identified subgroups and as a blueprint for innovative future trials to individualise prevention and therapy. Patient involvement is key in every part of iCARE4CVD (e.g. patient advisory board, country-specific Patient Panels) to build a motivational framework for self-care by patients. The project brings together an EU-wide consortium with the needed resources and expertise from the public and private side to bring iCARE4CVD to success.

Keywords: prevention,heart failure,diagnosis,risk stratification,treatment response,patient engagement
Extending light wave scanning tunnelling microscopy to ultrafast transport phenomena (ELISTRA)

Framework: Horizon Europe — Excellent Science
Programme: Marie Skłodowska-Curie Actions (MSCA)
Theme: Marie Skłodowska-Curie
Destination: Postdoctoral Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Physics
Countries involved: Germany
Call: MSCA Postdoctoral Fellowships 2023 (HORIZON-MSCA-2023-PF-01, 2023)
Start date: 2024-05-15
End date: 2026-05-14
Duration (months): 24.0
Total project cost (EUR): 189687.36
EU funding (EUR): 189687.36
Participants: 1
Project status: SIGNED

Unravelling the fundamental phenomena of electron motion on its intrinsic time and length scales is a vital pre-requisite for technological applications as dynamics of quantum systems are largely determined by ultrafast processes occurring on sub-picosecond time and atomic length scales. ELISTRA will gain unprecedented access to the ultrafast physics of ballistic electron transport through free-standing graphene nanoribbons (GNRs) with atomic scale control by combining for the first time scanning tunnelling microscope (STM) transport experiments with sub-cycle THz laser pulses funnelled into the STM junction (light wave STM). To achieve this, single atomically precise GNRs are positioned with sub-nanometre control in a transport configuration bridging tip and substrate of an STM. THz radiation funnelled into the tunnelling junction acts as an ultrafast bias modulation driving electronic currents by opening selective transport channels on the intrinsic time scales of electron motion and tunnelling processes. Using pump-probe schemes, the project will explore the sub-picosecond time evolution of coupling of electrons traversing the ribbon with fundamental excitations like phonon modes. These experiments reveal questions about the possibility to control and modify electronic degrees of freedom beyond electron motion by THz radiation. ELISTRA will synergistically combine light wave STM, pioneered by the host institution, and STM transport experiments, in which the applicant presents outstanding skills. The project enables the applicant gathering proficiency in the rapidly emerging field combining ultrafast with atomic-scale physics. Building upon his existing expertise, the training will sharpen the applicant’s scientific profile and improve his employment perspectives by emerging him in a host institution, that continuously drives the interdisciplinary frontier of nanoscopic measurements.

Keywords: scanning tunnelling microscopy,scanning tunnelling spectroscopy,ultrafast electron dynamics,thz frequency,graphene nanoribbons,plasmonics,ballistic transport