Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Doctoral Network on Enabling Scaled Production of Durable Natural Fibre Components (ENDURE)

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: Information Science and Engineering
Countries involved: Denmark,Sweden,France,Spain
Call: MSCA Doctoral Networks 2024 (HORIZON-MSCA-2024-DN-01, 2024)
Start date: 2026-01-01
End date: 2029-12-31
Duration (months): 48.0
Total project cost (EUR): 3772132.2
EU funding (EUR): 3772132.2
Participants: 15
Project status: SIGNED

The European moulded fibre products (MFP) manufacturing sector has global technology leadership. Job creation and sustainable growth in this sector contributes to the Green, Circularity and Digital Transition of the European economy. To succeed on the ambitious objectives set in the European Green Deal, the European natural fibre material (NFM) processing industry and the European moulded fibre products manufacturing industry must have access to a new generation of innovative, entrepreneurial, highly skilled research-oriented cross-disciplinary engineers. The ENDURE doctoral network aims to train 12 Doctoral Candidates on cross-disciplinary topics of: (i) natural fiber-based materials engineering; (ii) product design and production engineering with fiber-based materials; (iii) digital manufacturing technologies and Industry 4.0 for the natural fiber industry. The eventual hybrid cross-disciplinary profiles of the DCs of ENDURE are currently extremely rare or not available as existing doctoral programmes in EU focus only on the individual aspects. Manufacturing firms dealing with the fibre materials thus currently suffer the lack of skilled personnel. A detailed understanding of the behaviour of new NFMs in production and design implications for MFPs will be developed within ENDURE. The project will foster innovations in NFM processing (using agricultural wastes, short fiber sources like eucalyptus, and recycled MFPs), in design and assembly of new production equipment for MFPs, in modelling solutions (both multiphysics and AI/ML based) for optimizing production, and deployment of sensors and digital twins. The methods will be used for demonstrator MFP production across five industry sectors. Successful completion of ENDURE will (i) expand the use of fibre-based materials from 2D packaging to 3D products; (ii) adopt the relevant digital technologies for the engineering of natural fibre-based products; (iii) digitalize the fibre-based materials moulding processes.

Keywords: moulded fibre products natural fibre materials wet moulding pulp moulding
Scientific basis for tungsten and tungsten alloys tailored for electron beam additive manufacturing (ElectronsMatter)

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: Information Science and Engineering
Countries involved: Sweden,Germany,Czechia,Italy,Spain,Finland,United States,Austria
Call: MSCA Doctoral Networks 2024 (HORIZON-MSCA-2024-DN-01, 2024)
Start date: 2026-01-01
End date: 2029-12-31
Duration (months): 48.0
Total project cost (EUR): 2688672.96
EU funding (EUR): 2688672.96
Participants: 15
Project status: SIGNED

The ElectronsMatter MSCA Doctoral Network addresses critical challenges in the additive manufacturing (AM) of tungsten and tungsten alloys, a field crucial for advancing applications in energy, aerospace, and green technologies. Tungsten, with its exceptional properties such as the highest melting point of any metal and excellent resistance to wear and corrosion, is ideal for extreme environments. However, its high melting temperature and brittleness make it difficult to process using conventional methods, limiting its industrial use. This project leverages electron beam powder bed fusion (PBF-EB), an AM technology with unique capabilities for processing refractory materials like tungsten. By combining computational modeling, advanced characterization, process design, novel in-process monitoring methods, and mechanical behavior analysis, ElectronsMatter aims to develop optimized strategies for manufacturing dense, crack-free tungsten components with complex geometries. The network will tackle key challenges such as defect formation, microstructure evolution, and process monitoring, driving innovations in AM and materials design. Furthermore, material reusability will be studied, enhancing the sustainability of the process. ElectronsMatter integrates the expertise of leading academic and industrial partners to train a new generation of materials scientists. Doctoral Candidates will benefit from interdisciplinary research, industrial secondments, and cutting-edge training in sustainability, innovation, and advanced manufacturing. This aligns with the MSCA Work Programme by fostering skills for the green and digital transitions and strengthening Europe’s competitiveness in sustainable manufacturing technologies. By addressing the technical, environmental, and societal challenges in AM, ElectronsMatter will not only advance materials science but also prepare a future-ready workforce equipped to meet the demands of a rapidly evolving industrial landscape.

Keywords: tungsten tungsten alloys electron beam additive manufacturing advanced characterization synchrotron techniques computational design structure modeling process monitoring mechanical performance
Embodied Social Experiences in Hybrid Shared Spaces (SHARESPACE)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Digital, Industry and Space
Theme: Digital
Destination: A human-centred and ethical development of digital and industrial technologies
Action type: Research and Innovation actions
Countries involved: Germany,France,Netherlands,Austria,Spain,United Kingdom,Italy,Latvia,Cyprus
Call: eXtended Reality Technologies (RIA) (HORIZON-CL4-2022-HUMAN-01, 2022)
Start date: 2023-01-01
End date: 2025-12-31
Duration (months): 36.0
Total project cost (EUR): 5947573.5
EU funding (EUR): 5947573.5
Participants: 16
Project status: SIGNED

SHARESHARESPACE will demonstrate a radically new technology for promoting ethical and social interaction in eXtended Reality (XR) Shared Hybrid Spaces (SHS), anchored in human sensorimotor communication. Our core concept is to identify and segment social sensorimotor primitives and reconstruct them in hybrid settings to build continuous, embodied, and rich human- avatar experiences. To achieve this, three interconnected science-towards-technology breakthroughs will be delivered: novel computational cognitive architectures, a unique self-calibrating body sensor network, and a fully mobile spatial Augmented Reality (AR) and virtual human rendering. We will create a library of social motion primitives and use them to design AI-based architectures of our artificial agents. SHARESPACE mobile capturing technologies combine loosely-coupled visual-inertial tracking of full body kinematic, hand pose and facial expression, incorporating novel neural encoding/decoding functionalities, together with local context-aware animations and highly realistic neural rendering. Our technology will be iteratively tested in 2 Proofs-of-principles involving human and artificial agents interacting in SHS, and 3 real-world use case scenarios in Health, Sport and Art. We will demonstrate a fully functional prototype of SHARESPACE tailored to the agents’ personalized characteristics (gender, culture, and social dispositions). SHARESPACE will support community-building and exploitation with concrete initiatives, including (i) public engagement around our research and innovation, (ii) promoting high-tech innovation and early transfer to our deep-tech companies, as premises for the consolidation of human-centric and sovereign European market areas such Industry AR and SHS, eHealth and tele-Health. Our long-term vision is to bring XR to a radically new level of presence and sociality by reconstructing sensorimotor primitives that enable ethical, trusted and inclusive modes of social interaction.

Keywords: embodied shared spaces,sensori motor primitives,synchronization,amplification,digital avatars,ego centric kinematics capturing,inclusive and ethical hybrid space,
"AREYLight AI: AI-Driven Smart City Solutions for Sustainable Urban Infrastructure" (AREYLight AI)

Framework: Horizon Europe — Innovative Europe
Programme: The European Innovation Council (EIC)
Theme: EIC Accelerator
Destination: Other destinations
Action type: EIC actions
Countries involved: Türkiye
Call: EIC Accelerator 2024 - Short application (HORIZON-EIC-2024-ACCELERATOR-01, 2024)
Duration (months): 12.0
Total project cost (EUR): 4000000.0
EU funding (EUR): 4000000.0
Participants: 1
Project status: SIGNED

AREYLight AI is transforming urban infrastructure through its innovative AI-driven smart city solutions. By integrating advanced AI algorithms, IoT sensors, and data analytics, AREYLight AI is a technology company that develops smart city solutions aligned with the European Union’s vision for digital and sustainable cities. The company specializes in AI-powered smart lighting systems, IoT (Internet of Things) integration, and infrastructure projects focused on energy efficiency. AREYLight AI's solutions directly support the EU's Green Deal and Digital Transformation strategies by helping cities reduce energy consumption, lower carbon emissions, and optimize infrastructure management. One of the company's primary goals is to enhance urban infrastructure through the use of intelligent technologies, such as sensors, communication networks, and AI-driven data analysis. These technologies enable cities to operate more efficiently, with real-time monitoring and dynamic adjustments in key areas like street lighting, traffic management, and environmental control. AREYLight AI also develops solutions for airports, ports, and cultural centers, offering comprehensive tools for energy management and sustainability. In line with the European Union’s sustainability goals, AREYLight AI’s technology helps reduce operational costs while contributing to climate action by minimizing carbon footprints. The company's innovations are designed to seamlessly integrate with existing urban infrastructure, making them adaptable and scalable for cities of all sizes. AREYLight AI is actively engaged in pilot projects and collaborations across the EU, working with governments, municipalities, and private sector partners to implement its solutions. By focusing on smart city technologies that contribute to energy efficiency and urban sustainability, the company aims to support the EU’s long-term objectives for cleaner, smarter, and more resilient cities.

Keywords: smart city,ai,iot,energy efficiency,predictive maintenance,sustainability,climate action,urban infrastructure,smart lighting,carbon reduction,smart sensors,green deal,digital transformatio
Deep Learning meets Behavioural Ecology in the wild: methodological applications using the sociable weaver (DeepWeaver)

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: Portugal,France,South Africa,Switzerland
Call: MSCA Staff Exchanges 2023 (HORIZON-MSCA-2023-SE-01, 2023)
Start date: 2024-08-01
End date: 2028-07-31
Duration (months): 48.0
Total project cost (EUR): 202400.0
EU funding (EUR): 202400.0
Participants: 4
Project status: SIGNED

Studies of wild animals, from conservation to behaviour, are usually based on individually marked animals. This requires capturing, marking and sampling animals, which imposes limitations as these methods can be challenging, time consuming and impact individual welfare. Additionally, following and observing or video recording animals to obtain data is further constraining. Recent developments in artificial intelligence, in particular deep learning, have the potential do radically and rapidly change the way in which animals are studied in the wild. These new methods can push current boundaries by allowing not only less invasive methods of identification, but also obtaining large volumes of data and, importantly, collection of new types of data, allowing new questions to be addressed. In this proposal, we bring together a team of scientist and technical staff from three European countries and South Africa. Our aim is to develop highly innovative methods, based on rapidly advancing developments in deep learning, which can have a substantial impact on the study of wildlife biology. Specifically, we will streamline non-invasive methods (i.e. no capture) in order to obtain 1) individual re/identification in the field; 2) identification of individual attributes (e.g. sex, size); 3) automatic identification of behaviours (e.g. provisioning young, aggression). In addition 4) we will establish a pipeline to process large volumes of video data, combining individual and behavioural identification. The project is based on exchanges between staff with different expertise, and on work conducted both in the lab and in field. These exchanges are expected to boost creativity and result in meaningful skills transfer and a strengthened collaborative network. The expertise and the methods developed will have a meaningful and lasting impact in the field of behavioural and wildlife biology, contributing to increase Europe’s competitiveness and attractiveness.

Keywords: automated behaviour detection,behavioural ecology,cooperation,deep learning,free ranging animals,machine learning
Surrogate modelling for 3D-printed, achromatic, high numerical aperture metafibres (SUPREME)

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: 2024-08-01
End date: 2026-07-31
Duration (months): 24.0
Total project cost (EUR): 189687.36
EU funding (EUR): 189687.36
Participants: 1
Project status: SIGNED

With the proposed research project, I aim to revolutionize optical metasurface design leveraging surrogate modelling techniques (OBJ1) towards the development of 3D-printed, achromatic, high numerical aperture (NA) metalens-enhanced fibres, called metafibres (OBJ2). The proposed methodology consists of three interconnected phases: firstly (WP1), constructing a supercell meta-atom library consisting of three-dimensional metaatoms through iterative optimization. The simulated designs will be 3D-printed and the simulation model updated based on the results of the experimental characterization, ensuring precise and realistic control of meta-atom responses. Secondly (WP2), a Gaussian Process Regression (GPR) will be implemented as a versatile surrogate model using the established supercell library. This machine learning technique enables the efficient prediction of complex optical meta supercell responses, facilitating rapid prototyping and customization with reduced computational overhead. Notably, GPR models allow to consider fabrication tolerances straight-forward in combination with data augmentation techniques. Lastly (WP3), I will exploit the GPR model for the design of high-performing achromatic metafibres, utilizing 3D-printing technology to directly print the metalenses on the tip of optical fibres. I have chosen a top research centre, Leibniz Institute of Photonic Technology/ Jena, Germany, to develop my MSCA project under supervision of a world-leading expert in optical fiber photonics. Using my knowledge in engineering, photonics and numerical simulation tools, this MSCA project will pave the way for metafibres promising versatile and broadband optical solutions with the potential to transform fields like microscopy, telecommunications and medical imaging. This research aligns with sustainability goals by minimizing material waste and energy consumption in the fabrication process, marking a significant advancement in metasurface and optical system design.

Keywords: metasurfaces,metalens,optical fiber technology,optical imaging,optical 3d printing,two photon polymerization,nanophotonics
Time-based single molecule nanolocalization for live cell imaging (TimeNanoLive)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: Systems and Communication Engineering
Panel description: Electrical, electronic, communication, optical and systems engineering
Countries involved: France
Call: ERC ADVANCED GRANTS (ERC-2022-ADG, 2022)
Start date: 2023-11-01
End date: 2028-10-31
Duration (months): 60.0
Total project cost (EUR): 2498196.0
EU funding (EUR): 2498196.0
Participants: 1
Project status: SIGNED

Despite the tremendous advances in single molecule localization microscopy mainly obtained on fixed cells, a major step is highly needed to transform it into a genuine live-cell nanoscopy allowing to understand biological processes in their full multi-scale nature from the individual molecule, to the cell, to the multicellular tissues. Currently, there is no solution to image with an acquisition speed compatible with the dynamics of living cells (>kHz), over a large volumes (>10000 μm3), with a significant in-depth imaging capability (>10 µm) without compromising the resolution (<10 nm) especially in the axial dimension. I will demonstrate that these challenges can be met without trade-off by proposing a disruptive approach which requires the entire illumination and detection strategies to be considered anew. Building on my achievements in super-resolution microscopy, I propose a disruptive optical implementation where a full-time coding approach allows to retrieve the space information, not only meeting the needed acquisition rate, but also bringing the richness of functional information (spectral, lifetime). In a first conceptual breakthrough, a new sweeping modulated illumination is introduced, where each point along the direction of the modulation can be retrieved through a unique frequency, without any ambiguity. By applying this frequency tagging in all dimensions, every single molecule event is described by a unique set of 3 frequencies. This unicity triggers a second change of paradigm, as emitters positions within a large field of view can now be retrieved in a camera-free setting. Fast acquisition can be performed by single monodetector, but the power of this temporal approach will be decupled by the ultimate technical advances of new neuromorphic detections. This unique in-depth information at the nanoscale will allow to finally decipher the structural and functional interplay in key biological mechanisms in living cells with unprecedented benefits.

Keywords: microscopy,super resolution,spectroscopy,live cell imaging
Streamlining Geo mapping and Early Monitoring with an All-in-One Data Collection System for power line and mining industries (IMC Aerie)

Framework: Horizon Europe — Innovative Europe
Programme: The European Innovation Council (EIC)
Theme: EIC Accelerator
Destination: Open to supporting projects in all areas of science, technology,...
Action type: EIC actions
Countries involved: Lithuania
Call: EIC Accelerator Open 2024 (HORIZON-EIC-2024-ACCELERATOR-02, 2024)
Start date: 2024-11-01
End date: 2026-10-31
Duration (months): 24.0
Total project cost (EUR): 3411514.31
EU funding (EUR): 2388060.02
Participants: 1
Project status: SIGNED

Power line and mining industries face challenges related to vegetation encroachment and infrastructure monitoring. The inefficient monitoring of vegetation growth near power lines increases the risk of wildfires, while inadequate monitoring of mining infrastructure can lead to safety hazards and operational inefficiencies. The current solutions are often inefficient due to their high operational costs, time-consumption and low-quality output, since most of them are custom built for the specific application of end user. Therefore, by combining advanced sensor fusion technology and real-time monitoring AISPECO innovation IMC Aerie, offers a comprehensive and cost-efficient solution. The system's controller allows integration of various sensors, creating a live Digital Twin enabling efficient vegetation management and infrastructure integrity eliminating wildfire and slopes sliding risks offering safety improved operational efficiency. It follows principles of digitalization and implements Industry 5.0 standards, European Green Deal- reducing GHG & black carbon emissions, and contributes to SDGs.

Keywords: sensor fusion,digital twin,real time inspection,lidar,hyperspectral imaging edge computing,power lines management,rail infrastructure,network infrastructures,energy efficiency,forestry,envir
Advanced breeding technologies aimed at producing highly nutritious, productive, and climate resilient new crops (F1 hybrid)

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): 24.0
Total project cost (EUR): 2500000.0
EU funding (EUR): 2500000.0
Participants: 1
Project status: SIGNED

The global agricultural sector is under pressure as climate change threatens crop yields and food security. Quinoa, with its nutritional value and adaptability, offers a promising solution, but the market faces challenges such as limited high-performing varieties, insufficient breeding technologies, and difficulties in scaling production. These issues highlight the urgent need for innovative solutions to develop resilient, high-yield quinoa varieties that also ensure environmental sustainability.Radicle Crops is uniquely positioned to address these challenges with its cutting-edge breeding technology designed to transform quinoa cultivation. Leveraging over 30 years of expertise and research from Wageningen University, we have developed a robust portfolio of 10 patented saponin-free quinoa varieties that offer superior nutritional value and resistance to environmental stressors. Our technological advancements include high-density marker panels for precise genetic mapping, bioinformatic pipelines for efficient data analysis, and computer vision phenotyping tools that allow rapid and accurate assessment of crop traits. A key innovation is our CMS-based hybrid breeding system, which enables the development of first-generation hybrids with significantly enhanced yield potential and climate resilience. This system is complemented by our universal gene-editing platform, which allows the creation of de novo cytoplasmic male sterility (CMS) and nuclear maintainer/restorer genetic complexes. This technology facilitates the production of hybrid seeds from scratch, enhancing the genetic diversity of quinoa and optimizing it for various global environments. By addressing the core challenges of the quinoa market with these advanced solutions, Radicle Crops is paving the way for more sustainable, resilient, and productive quinoa cultivation on a global scale.

Keywords: cms technology,precision agriculture,biotechnology,plant genetics,botany