Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Innovating with nature for sustainable water management in the global south (NEUTRAL4GS)

Framework: Horizon Europe — Excellent Science
Programme: Marie Skłodowska-Curie Actions (MSCA)
Theme: Marie Skłodowska-Curie
Destination: Staff Exchanges
Action type: Marie Skłodowska-Curie actions
Panel: Environment and Geosciences
Countries involved: Denmark,Czechia,Italy,Portugal,Colombia,Indonesia,Thailand
Call: MSCA Staff Exchanges 2023 (HORIZON-MSCA-2023-SE-01, 2023)
Start date: 2025-01-01
End date: 2028-12-31
Duration (months): 48.0
Total project cost (EUR): 801714.29
EU funding (EUR): 740600.0
Participants: 8
Project status: SIGNED

Water, particularly access to safe drinking water and sanitation remains a worldwide challenge. By 2040, it is estimated that 1 in 4 children will be living in regions of extremely high-water stress because of overuse, population growth, and climate change. One of the regions most affected by these issues is the Global South. An inclusive approach for managing water resources circularly is needed to address the clean water crisis. Here, the expertise from the European Union countries can support the research needs and knowledge gaps from the Global South, while simultaneously leading to an assessment of current challenges and best practises in the Global North. For that, 6 academic institutions, 1 SME and 1 water utility join efforts through NEUTRAL4GS. By implementing co-creation and co-design strategies between partners from the Global South and EU, the project aims to develop and test solutions inspired by nature for urban water management. This includes jointly working with i) different types of urban water (stormwater, greywater and wastewater), as well as with ii) a range of different treatment technologies combining nature-based solutions with supporting technological units (e.g., membranes, nanofiber biomass carriers, graphene-based nanocomposites, lightweight porous media or photocatalysis) that can be innovated for more sustainable or close to nature performance to deliver treated water and water for reuse. Holistic sustainability and economic assessments will guide the development and prioritization of technologies. Thus, NEUTRAL4GS will pioneer innovative solutions in water treatment, ensure social acceptance and adoption of technologies, and generate significant impacts in terms of societal, environmental, and public-health benefits. By garnering awareness and involving the local authorities and local community in the process, NEUTRAL4GS strive to ensure sustainability and long-term success of the project’s outcomes beyond its lifetime.

Keywords: water management,wastewater,pollutants,water quality,nature based solutions,
Innovative tools to treat and model complex cancer environments (TheraTools)

Framework: Horizon Europe — Excellent Science
Programme: Marie Skłodowska-Curie Actions (MSCA)
Theme: Marie Skłodowska-Curie
Destination: Doctoral Networks
Action type: Marie Skłodowska-Curie actions
Panel: Life Sciences
Countries involved: Spain,Italy,Portugal,Germany,Cyprus,Israel
Call: MSCA Doctoral Networks 2021 (HORIZON-MSCA-2021-DN-01, 2021)
Start date: 2023-01-01
End date: 2026-12-31
Duration (months): 48.0
Total project cost (EUR): 2446223.66
EU funding (EUR): 2291119.2
Participants: 13
Project status: SIGNED

TheraTools has arisen as a multidisciplinary research and training network that encompasses a full academical and technological view of the development of scientific tools for the comprehensive research of malignant tumors localized beyond a biological barrier, as in brain tumors. This challenging objective needs of the concerted effort of both academic and industrial organizations. As such, TheraTools is formed by a consortium composed by (a) four academic beneficiaries(POLYMAT-University of the Basque Country, Spain; University of Aveiro, Portugal; Italian Institute of Technology, linked to Sant´Anna School of Advanced Studies, Italy, and Technion – Israel Institute of Technology, Israel); and (b) 6 industrial partners: Polimerbio (Spain), BEONCHIP (Spain), Metatissue (Portugal), Vetex (Cyprus), I+Med (Spain), and Nanoscribe (Germany). All the partners will be involved in both research and training activities framed within this network. TheraTools consortium and working plan has been configured to stablish a supportive network within a EJD in the topic of the development of “Innovative tools to treat and model complex cancer environments”. This network considers the engagement of 9 early-stage researchers that will have the opportunity to be awarded with double doctorate degrees in two different countries. TheraTools network will offer to the ESRs high quality training opportunities across several disciplines to conceive a full view of the development of therapeutics, from the synthesis of the drugs to their validation in in-vitro models. In its endeavor to translate the experience of the participants into products for health benefit, TheraTools will transfer the knowledge and competences to young researchers, providing them with enhanced career perspectives in both the academic and non-academic sectors through international, interdisciplinary, and inter-sectorial mobility combined with an innovation-oriented mindset and an excellence level of training.

Keywords: polymer based formulations for nanotherapy,blood brain barrier,microfluidics,3d printing,glioblastoma in vitro models
Computational framework to assess brain maturation in small vulnerable newborns, from womb to cot (WOMB2COT)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting 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: United Kingdom
Call: ERC STARTING GRANTS (ERC-2025-STG, 2025)
Start date: 2026-05-01
End date: 2031-04-30
Duration (months): 60.0
Total project cost (EUR): 1499990.0
EU funding (EUR): 1499990.0
Participants: 1
Project status: SIGNED

Over 25% of infants worldwide are born too soon and/or too small due to adverse exposures during pregnancy, such as maternal malnutrition and infections. Such exposures can also disrupt the maturation of the fetal brain, which is rapidly developing during pregnancy and the first year of life. Hence, these small vulnerable newborns (SVNs), if they survive, are at high risk of poor neurodevelopmental outcomes in later life. Monitoring anatomical growth is key to optimising and determining SVN care pathways, especially in the first days after birth. Ultrasound (US) enables non-invasive imaging of fetal and neonatal brain anatomy, but growth assessments are based on coarse metrics (e.g., head circumference), with pre- and post-birth measurements rarely integrated. WOMB2COT will tackle these hurdles with a technically ambitious programme that combines US imaging with deep learning (DL) and computational neuroanatomy. We will develop advanced DL-based US image analysis techniques, including neural radiance fields, image registration, and domain adaptation, to quantify brain development in the most vulnerable preterm infants compared to their expected in utero growth trajectory. This approach will utilise longitudinal cUS scans collected in neonatal intensive care units (NICUs), offering a more detailed, objective evaluation of neonatal brain growth and bridging the care gap as these infants transition from intra- to extra-uterine life. We aim to reduce US imaging artefacts (e.g., acoustic shadows) and enhance structural specificity to sub-millimetre resolution to extract brain morphometrics (BMs), surpassing coarse and qualitative assessments. Building on our population atlas of healthy brain maturation (Nature 2023) and advanced computational tools, we will compare SVN growth with age-matched healthy fetuses. To maximise its diagnostic utility, WOMB2COT will be developed for low-cost, point-of-care US equipment, benefiting regions with the highest SVN burden.

Keywords: ultrasound brain development deep learning medical image analysis segmentation fetus neonate preterm birth fetal growth restriction
Elucidating inner cells contribution to pavement cell shape acquisition in Arabidopsis (iCON)

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: Sweden
Call: MSCA Postdoctoral Fellowships 2023 (HORIZON-MSCA-2023-PF-01, 2023)
Start date: 2025-06-23
End date: 2027-06-22
Duration (months): 24.0
Total project cost (EUR): 222727.68
EU funding (EUR): 222727.68
Participants: 1
Project status: SIGNED

In plants, the outermost epidermal cell layer is critical for protecting the entire plant against external threats such as rain, wind and pathogens. The plant epidermis is a complex tissue consisting of multiple cell types, all with different shapes, functions and developmental trajectories. Although studied in isolation, our understanding of how these cells interact to ensure tissue integrity is poor, but at present, the outermost jigsaw-puzzle-shaped pavement cells have emerged as key players. Recent findings in the host lab suggest that the diverse physical and/or mechanochemical nature of the cell wall is crucial for pavement cell-shape acquisition, and thus under influence of the underlying tissue layers. However, yet the identity of the putative signals derived from inner cell layers, defining the shape of epidermal cells and the integrity of the multilayered leaf tissue, remains to be explored. Hence, in iCON I will join the Robert (host) lab to disentangle the signaling networks and mechanical constraints of inner mesophyll cells that determine epidermal pavement cell shape and organogenesis of the leaf, using a suite of novel and multidisciplinary approaches in the model plant Arabidopsis thaliana. Specifically, I will acquire new skills in cutting-edge microscopy, cell biology and biomechanics to generate a high-resolution 3D map and uncover mechanical/physical cues, and leverage my expertise in transcriptomics, genetics and molecular biology to determine molecular components, together allowing me to decipher the overall mechanism via which mesophyll cells orchestrate pavement cell shape acquisition. Besides contributing new knowledge, iCON will allow me to expand my scientific expertise and gain key transferrable skills, boosting my strive to become a research leader. Ultimately, knowledge on how plants maintain tissue integrity can support the development of stress-resilient plants and thus contribute to a sustainable agriculture in a changing climate.

Keywords: epidermal pavement cell,mesophyll cell,cell to cell communication,periclinal cell wall,mechanical cues,molecular signaling,stress resilient crop
Gradual integration of REnewable non-fossil ENergy sources and modular HEATing technologies in EAF for progressive CO2 decrease (GreenHeatEAF)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Digital, Industry and Space
Theme: Industry
Destination: Climate neutral, Circular and Digitised Production
Action type: Innovation actions
Partnership: Clean Steel (co-programmed)
Countries involved: Italy,Germany,Sweden,Spain,Belgium,Norway
Call: Modular and hybrid heating technologies in steel production (Clean Steel Partnership) (IA) (HORIZON-CL4-2022-TWIN-TRANSITION-01, 2022)
Start date: 2023-01-01
End date: 2026-12-31
Duration (months): 48.0
Total project cost (EUR): 4099693.75
EU funding (EUR): 3564245.25
Participants: 14
Project status: SIGNED

EAF steelmaking is the key technology for decarbonised steelmaking, either in scrap-based plant by modification of existing processes for further decarbonisation, or as new EAF installations in decarbonised integrated steel works to (partly) replace the classical BF-BOF production. At same time the EAF is the most important example for modular and hybrid heating, already now combining electric arc heating with burner technologies. Consequently, it was selected as main focus of GreenHeatEAF for the Call „Modular and hybrid heating technologies in steel production“. GreenHeatEAF develops and demonstrates the most important decarbonisation approaches at EAFs including the use of hydrogen to replace natural gas combustion in existing or re-vamped burners or innovative technologies like CoJet. Furthermore, decarbonisation of EAF steelmaking by solid materials like DRI/HBI and renewable carbon sources like biochar is tackled. Technologies to re-optimise the heating management with maximum heat recovery of off-gas and slag employing new sensor and soft-sensor concepts as well as extended digital twins are developed: as result the extended CFD and flowsheeting models, and monitoring and control tools will prognose the influences of the different decarbonisation measures on EAF and process chain to support upcoming decarbonisation investments and to enable the control of decarbonised hybrid heating with maximum energy efficiency. GreenHeatEAF combines trials in demonstration scale, e.g. in combustion- and EAF-demo plants, with validations in industrial scale and digital optimisations with high synergy. Thus, it completely follows the Horizon Twin Transition and Clean Steel Partnership objectives and the target to progress decarbonisation technologies from TRL 5 to 7. This synergic concept of GreenHeatEAF supports implementation and digitisation to speed up the transition of the European steel industry to highly competitive energy-efficient decarbonised steel productio

Keywords: decarbonisation,regenerative heating,hydrogen enhanced combustion,burner retrofit,oxygen enrichment,alternative c sources,biomass,model predictive control,heat recovery,energy efficiency
Leveraging Precision in Numerical Optimization for Robotic Motions (LP-NORM)

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: Information Science and Engineering
Countries involved: France
Call: MSCA Postdoctoral Fellowships 2021 (HORIZON-MSCA-2021-PF-01, 2021)
Start date: 2022-08-01
End date: 2024-07-31
Duration (months): 24.0
Total project cost (EUR): 211754.88
EU funding (EUR): 211754.88
Participants: 1
Project status: CLOSED

Automated vehicles and complex robot workers are expected to be used massively soon, with positive impacts on security, health at work and productivity. To handle real-world situations, they need to compute their command as fast as possible, but the advanced, safe control algorithms remain a computational bottleneck. To find the solution to a set of motion specifications and constraints for a robot, a widely used approach is to formulate and solve an optimization problem. The formulation is necessarily imprecise, due to modeling, sensing and estimation errors and the solution will not be executed perfectly by the robot. Yet the optimization solvers used in robotics are designed to converge to an exact solution with high precision, wasting time. In this project, I make a change of paradigm by leveraging approximations and investigate how the absence of need for high precision can be used to develop faster solvers. I study what approximations or errors are acceptable for the problem formulation and the solution, paying attention to the numeric properties of the problem. I use this knowledge to develop a solver tailored for approximate computations, with an emphasize on cheap but imprecise inner iterations and early termination. It will also handle gracefully infeasible situations due to errors, making it safer to operate in real conditions. To make the study, and test and benchmark the solver, I focus on two families of control problems: model predictive control and instantaneous linearized control, applied to a wide variety of systems, from buses, to rockets, to humanoid robots. This solver will have important impacts: make it possible to achieve real-time control for the most complex system; allow to keep real-time, when it was already possible, while enriching the problems; reduce the computing power and energy consumption required for a given robot. Understanding and handling imprecisions would also allow to build less precise and thus cheaper robots.

Keywords: optimisation based control model predictive control whole body control autonomous vehicles quadruped robots humanoid robots
Advanced AI and RobotIcS for autonomous task pErformance (ARISE)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Digital, Industry and Space
Theme: Digital
Destination: Digital & Emerging Technologies for Competitiveness and Fit for the Green Deal
Action type: Research and Innovation actions
Partnership: AI-DATA-ROBOTICS (co-programmed)
Countries involved: Greece,Italy,Spain,Cyprus,Croatia,Germany,United Kingdom,France
Call: Novel paradigms and approaches, towards AI-driven autonomous robots (AI, data and robotics partnership) (RIA) (HORIZON-CL4-2023-DIGITAL-EMERGING-01, 2023)
Start date: 2024-01-01
End date: 2027-12-31
Duration (months): 48.0
Total project cost (EUR): 7146256.25
EU funding (EUR): 7146256.25
Participants: 16
Project status: SIGNED

Maintaining the competitiveness and leadership position of crucial industries such as renewable energy and agriculture, is contingent upon AI and Robotics increasingly becoming a widespread and integral part of the relevant technological landscapes, particularly in the face of steep labour shortages. ARISE project aims to introduce a combination of perception and control modules around a reconfigurable robotic manipulator that will enable a step change in the level of automation of complex manipulation tasks. ARISE will comprise the following key novel technology components that will significantly push the state of the art in terms of automatic task segmentation, human robot interaction and complex manipulation: (1) Two reconfigurable pneumatic-based robotic manipulators mounted on a mobile robotic platform (2) Novel soft end-effectors with variable stiffness that will allow for a diverse set of manipulation tasks (3) A Robotic perception module comprising 3D vision algorithms (4) A Localisation and Mapping module that will allow the robot to accurately identify its position within the environment (5) A Semantic Mapping module powered by scene understanding algorithms (6) A Knowledge Representation framework that will capture important information regarding objects’ properties and relationships (7) A Hierarchical Imitation Learning framework for acquiring robotic skills to accomplish complex tasks directly from human demonstrators (8) A Human-Interaction conditioned Path and Task planning module enabling reactive robot control (9) An edge-AI framework for deploying Machine Learning models and computer vision algorithms at the edge in a streamlined fashion. The ARISE toolchain will be integrated and validated in 5 real use case scenarios including installation and repair, and transplanting and harvesting tasks, in solar and hydroponic farms, respectively.
Lignin and Starch for Tinting Alternative Foods (LISTAF)

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: Chemistry
Countries involved: Sweden
Call: MSCA Postdoctoral Fellowships 2023 (HORIZON-MSCA-2023-PF-01, 2023)
Start date: 2025-01-02
End date: 2027-01-01
Duration (months): 24.0
Total project cost (EUR): 222727.68
EU funding (EUR): 222727.68
Participants: 1
Project status: CLOSED

The LISTAF project seeks to develop biodegradable photonic materials using starch and lignin as sustainable alternatives to conventional, non-biodegradable colorants in the food industry. These materials harness photonic color, which offers greater durability compared to pigment-based colors and finds applications across industries. The project centers on three key work packages: 1. Precision production of starch nanoparticles (SNPs) through enzyme-assisted techniques, with a focus on controlling amylopectin branching and optimizing self-assembly conditions. 2. Utilization of lignosulfonates and colloidal lignin as surfactants to stabilize SNPs, exploring variables such as concentration, pH, and addition timing to control SNP size and polydispersity. 3. Development of photonic starch and coatings for food industry applications, including in vitro digestion and fermentation analyses to assess nutritional advantages. Outstanding challenges to address include overcoming SNP aggregation, gaining control over nanoscale starch-lignin interactions, and achieving close-packed assembly of the particles. The project aims to address these challenges through enzyme-aided research and innovative bio-based surfactant systems. Ultimately, the goal is to create eco-friendly, cost-effective, and nutritionally valuable materials that align with consumer demand for high-quality food products. The successful completion of this project will provide me with valuable training in lignin chemistry and bio-photonics, while also enabling me to conduct groundbreaking research in the field of starch applications. This comprehensive experience will expand my research expertise, yield high-quality publications, and significantly enhance my prospects for securing a faculty position in the future.

Keywords: starch lignin food nutrition structural color photonic crystal glass