Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Photo & electrochemical Urea production by Recycling Emissions of CO2 and NOx (PURE-CO2 and NOx): Deciphering Mechanistic Insights of Urea Formation (PURE-CO2 and NOx)

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: Netherlands,United Kingdom
Call: MSCA Postdoctoral Fellowships 2024 (HORIZON-MSCA-2024-PF-01, 2024)
Start date: 2026-01-01
End date: 2027-12-31
Duration (months): 24.0
Total project cost (EUR): 276187.92
EU funding (EUR): 276187.92
Participants: 2
Project status: SIGNED

The PURE-CO2 and NOX project at Imperial College, London, aims to tackle the rising anthropogenic emissions of CO2 and NOx by pioneering a recycling solution that converts these gases into “urea” using photo and electrocatalytic processes. This multidisciplinary initiative merges the development of catalysts, reactor design, and unexplored in situ and operando spectroscopic studies to examine transient intermediates, reaction kinetics and pathways. The initial phase targets the identification of optimal cathode catalysts for the co-reduction of CO2 and NOx, focusing on the use of non-precious transition metals to synthesize a range of single atom catalysts. These are evaluated for their reduction efficacy alongside photoanode electrodes fabricated from n-Si and n-GaAs. Custom designed industrially relevant flow reactors then assess the reduction performance of these setups. Under Professor James Durrant’s supervision, rigorous in situ spectroscopic and time-resolved operando photoinduced absorption studies are conducted to elucidate the reaction intermediates, byproducts, reaction kinetics and feasible pathways. This innovative application of operando techniques to study the photo and electrocatalytic urea production reactions is novel and fills a significant gap in understanding both photo and electrocatalytic systems. The project holds potential to revolutionize the design of cost-effective, efficient catalysts, projecting an enhancement in reaction efficiency by 30-40%, potentially reducing urea production costs in industrial settings by 10-12%. This aligns closely with EU priorities, setting the stage for significant advancements in emission reduction technologies.

Keywords: photocatalysis electrocatalysis co2 reduction nox reduction urea production
The next leap in cancer care: combining multi-modality and spectral imaging, advanced therapies, robotics and AI to enable standardized, precise interventional oncology treatments for cancer patients (PreciseOnco)

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: Netherlands,Austria,Germany,France,Belgium,Italy
Call: Boosting innovation through better integration of fragmented health R&I efforts (HORIZON-JU-IHI-2025-09-single-stage, 2025)
Start date: 2026-01-01
End date: 2030-12-31
Duration (months): 60.0
Total project cost (EUR): 23928030.75
EU funding (EUR): 14917499.25
Participants: 14
Project status: SIGNED

Every year, millions of people around the world face a cancer diagnosis, and for many of them, precise and minimally invasive treatments offer the best hope for recovery. However, delivering these treatments accurately—especially deep inside the body—remains a major challenge. This project, PreciseOnco, aims to revolutionize how doctors plan, guide, and evaluate cancer therapies using the latest breakthroughs in medical imaging and robotics. At the heart of our work is a new generation of imaging technology, called spectral imaging, which can distinguish between different types of tissue and treatment materials with much greater clarity than current scans. This allows doctors to see tumors more clearly, guide needles with improved accuracy, and monitor treatments in real time. We will also introduce motion correction tools that account for patient breathing and other natural movements during procedures which make the scans sharper, faster, and more reliable. In addition, we will integrate robotic assistance into treatment workflows to help doctors place needles with sub-millimeter precision. This will reduce variability between operators, shorten procedure times, and make complex treatments more widely accessible, even in smaller hospitals. Our advanced software and AI tools will make it easier to plan, deliver, and confirm treatments without extra scans or delays. We will test these innovations in real-world clinical studies, including treatment of liver and kidney tumors, where today’s tools often fall short. Ultimately, PreciseOnco aims to make cancer interventions safer, more targeted, and more successful which will offer patients better outcomes with less burden.

Keywords: medical imaging interventional oncology precision medicine minimally invasive therapy multidisciplinary cancer care value based healthcare
Novel 3D skin model enabled by a breakthrough nanofiber scaffold (Gelatex)

Framework: Horizon Europe — Innovative Europe
Programme: The European Innovation Council (EIC)
Theme: EIC Accelerator
Destination: Other destinations
Action type: EIC actions
Countries involved: Estonia
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

Using animals for testing in cosmetics and pharmacological product development is a very sensitive and divisive issue today. Every year, 115M animals are used for drug and cosmetics development. The public pressure to reduce the usage of animals and avoid cruelty is increasing, and the regulators are taking actions. Worse, when it comes to skin testing, animal models are not the best choice. There are many unique aspects of human skin that cannot be replicated during animal testing. These include pigmentation, dermal evolution, adipose tissue presence, skin appendage distribution and others. Our core innovation is the unique nanofibre spinning technology called HaloSpinning. HaloSpinning is drastically different from state-of-the-art fibre spinning technologies such as electrospinning or wet-spinning. We further develop these HaloSpin nanofibres into state-of-the-art 3D scaffolds, which consist of a mixture of both synthetic polymers (PLGA, PLGA:PCL) and natural polymers (gelatin, collagen, chitosan, alginate). In this EIC Accelerator project we will industrialize HaloDerm—our breakthrough skin model enabled by HaloSpin nanofibre scaffolds.

Keywords: scaffold,skin model
Impact of Lipid Cell Composition on Beta-Amyloid Aggregation: Exploring Novel Therapeutic Targets for Alzheimer's Disease (ABlina)

Framework: Horizon Europe — Widening Participation and Strengthening the European Research Area
Programme: Widening participation and spreading excellence
Theme: Attracting and mobilising the best talents
Destination: Attracting and mobilising the best talents
Action type: Marie Skłodowska-Curie actions
Panel: Life Sciences
Countries involved: Portugal
Call: ERA Fellowships (HORIZON-WIDERA-2024-TALENTS-02, 2024)
Start date: 2025-07-01
End date: 2027-06-30
Duration (months): 24.0
Total project cost (EUR): 191343.12
EU funding (EUR): 191343.12
Participants: 1
Project status: SIGNED

The ABlina project aims to study how cell membrane lipid composition affects the formation and deposition of beta amyloid (Aβ) aggregates. To achieve this, Molecular Dynamics (MD) simulations will be performed on membranes with varying lipid compositions, focusing on models that mimic senescent and Alzheimer's disease cells. The data generated will contribute to the establishment of a database, which will be subsequently analysed, to identify lipid patterns capable of modulating the behaviour of Aβ aggregation. If lipids promoting aggregation are identified, novel drugs could be formulated to inhibit their synthesis or interaction with Aβs, thereby preventing aggregation. Conversely, if any lipid is found to avoid aggregation, strategies could be designed to augment its presence within cerebral cells. To address the inherent spatial and temporal limitations of Molecular Dynamics (MD), Coarse-Grained (CG) modelling will be utilized. The project will be conducted at ITQB NOVA (University NOVA of Lisbon), under the supervision of Dr. Manuel N. Melo, a key contributor to the development of the original Martini Force Field, a widely recognized CG model that will be employed in this study. Through Dr. Melo's mentorship, I will receive advanced training in CG model development, enabling the accurate parameterization of lipids relevant to the project and enhancing the robustness of the database. The combination of Dr. Melo's extensive proficiency in CG methodologies and my prior experience in MD simulations and database management will establish a synergistic collaboration, expanding both my expertise and that of the host research group. Overall, my project employs an innovative approach to investigate the relationship between cell membrane composition and Aβ aggregation, potentially revealing lipid membrane composition as a promising therapeutic target against Alzheimer’s disease.

Keywords: lipidomics,amyloid beta,coarse grained
Refinement, Scale-up and Demonstration of a Cost-effective, Low-latency and Low-power Multi-purpose Processor Platform (QUAKE)

Framework: Horizon Europe — Innovative Europe
Programme: The European Innovation Council (EIC)
Theme: EIC Accelerator
Destination: Other destinations
Action type: EIC actions
Countries involved: United Kingdom
Call: EIC Accelerator 2025 - Short application (HORIZON-EIC-2025-ACCELERATOR-01, 2025)
Duration (months): 24.0
Total project cost (EUR): 2495000.0
EU funding (EUR): 2495000.0
Participants: 1
Project status: CLOSED

When selecting a processor for edge applications, electronics engineers are faced with a multi-dimensional optimisation problem, balancing performance, energy efficiency, footprint, cost and development time. Whilst ASICs (Application-Specific Integrated Circuit) are high-performance, development time is long, and they lack flexibility. Programmable platforms such as an FPGAs (Field-Programmable Gate Array) bring design flexibility but at the expense of performance and cost-effectiveness. QUAKE will redefine embedded computing on the edge by merging high-performance DSP (digital signal processing), low-energy AI (artificial intelligence), and software-defined I/O (Input/Output) on one homogeneous single-chip platform. Our approach typically cuts hardware part counts by up to 70 % and development cycles by over six months, unlocking electronics development projects that would otherwise be too time-consuming or expensive. This project will deliver a fully validated next-generation XCORE processor and supporting SDK that will establish XMOS as a market leader in energy-efficient, software-defined silicon for edge AI and control applications. Building on validated prototypes and an extensive patent portfolio, the project will complete the 16nm tape-out, validate on-chip performance and integrate full compliance with RISC-V, fully aligning our platform with sectors favouring open toolchains and interoperability. By coupling deterministic multi-threading, DSP and AI inference with RISC-V and proprietary extensions, the platform achieves up to 4x DSP/AI throughput and 16x I/O performance compared to leading microcontroller-based platforms while operating on similar power budgets. With established silicon partners and proven market traction, XMOS is well placed to scale this innovation globally and expand beyond professional audio into rapidly growing cross-sector domains including industrial automation, robotics, mobility, and connected consumer devices.

Keywords: deterministic processor architecture for low latency and real time applications,flexible software defined single chip platform for dsp ai control,platform for application specific customisation
gifted_GENE: The Pioneering Platform Enhancing Satellite Lifespan (gifted_GENE)

Framework: Horizon Europe — Innovative Europe
Programme: The European Innovation Council (EIC)
Theme: EIC Accelerator
Destination: Other destinations
Action type: EIC actions
Countries involved: Italy
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

We are Aiko, a deep tech software company founded in Turin in 2017 with currently presence also in France. Since our foundation, we are developing pioneering Artificial Intelligence technology for the automation of space missions. Today, we have become the leading provider of complex, AI-based solutions for space in the European ecosystem running more than 20 contracts with key commercial and institutional organizations from the space industry such as EutelSat OneWeb and ESA. We present gifted_GENE a breakthrough AI-driven software agnostic to satellite missions and powered by advanced automation algorithms and AI techniques to enhance efficiency and optimise the entire mission life cycle. Our solution provides data-driven analytics to increase the automation of the operation of satellites through AI-based telemetry analysis, early anomaly detection and classification, root cause analysis, and trend and pattern identification. gifted_GENE addresses the pains that satellite operators face for analysing the telemetry data of their space assets and identify failures, root causes and trends. Based on actual use cases, our solution has the potential to increase safety in operations (+150% anomalies detected compared to traditional methods) as well as predict and prevent anomalies (up to 4 days of early anomaly detection and, in specific scenarios, up to 2 months) extending the lifetime expectancy of satellites. Our target market is the LEO satellite market estimated to reach €259 billion in 2029. Our customers are satellite operators, targeting European LEO satellite operators for market penetration and development. Among our plans is to expand to the US market, as well as to the GEO satellite market. Based on our financial projections this project will result in €43 million cumulative revenues during the next 5 years with a 13% market share in terms of satellite operators using gifted_GENE to monitor and manage the health of their space assets

Keywords: artificial intelligence,machine learning,deep learning,satellite predictive maintenance,satellite telemetry data analysis,early failure identification,leo satellites
Revolutionizing Autonomous Mobility with Novel 10x High-Resolution Silicon Photonics Imaging RADAR Technology for Enhanced Safety and Efficiency. (SiPhoRadarTech)

Framework: Horizon Europe — Innovative Europe
Programme: The European Innovation Council (EIC)
Theme: EIC Accelerator
Destination: Other destinations
Action type: EIC actions
Countries involved: Germany
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 Society of Automotive Engineers (SAE) defines 6 levels of driving automation, ranging from fully manual (Level 0) to fully autonomous Level 5 (fully autonomous). From Level 3 and beyond the vehicle is considered under machine supervision, meaning the need for precise sensors is paramount. To bring a higher precision than a human driver, imaging technology and its corresponding sensors must provide reliable results in all conditions, particularly in bad lighting, heavy rain, or snow, which current cameras and LIDAR systems face performance issues. Xavveo proposes the SiPhoRadarTech, a groundbreaking 4D imaging RADAR system using Silicon Photonics technology. This system offers a 10x improvement in resolution (0.1°) over current RADAR technologies and a 360° panoramic view. The global autonomous vehicle market was valued at €48B in 2023, with a projected CAGR of 21.9% from 2023 to 2030. We target the Global Automotive Radar Sensors Market, currently valued at €6.3B, expected to reach €11.7B by 2030 with a CAGR of 10.94%. Xavveo's solution addresses critical limitations of current sensor technologies, ensuring higher reliability, cost efficiency, and robust performance under all conditions, making it a transformative technology for the autonomous vehicle and industry automation markets. Xavveo is led by its 3 co-founders: Dr. Sven Otte, CEO, 25 yrs of semiconductor and optical communications industry experience, Dr. Stefan Meister, CTO, 22 yrs of experience in Silicon Photonics and Fiber Optics, and Ulrich Keil, VP Engineering, 24 yrs of expertise in IC Design and optical transceiver development. This EIC Accelerator is stepping stone in Xavveo’s development by enabling us to reach series readiness and accelerate time to market, particularly finalise chip design and RADAR architecture, and collect field data.

Keywords: silicon photonics radar,4d imaging technology,autonomous vehicle sensors,weather resistant radar,high density point cloud
Malaria diagnosis and prognosis with an electrokinetic-driven aptamer-based lateral flow assay. (MalDiProT)

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: Spain,United States
Call: MSCA Postdoctoral Fellowships 2023 (HORIZON-MSCA-2023-PF-01, 2023)
Start date: 2024-10-01
End date: 2026-09-30
Duration (months): 24.0
Total project cost (EUR): 187858.56
EU funding (EUR): 187858.56
Participants: 2
Project status: SIGNED

Malaria remains a public health concern, with 247 million cases and 619,000 deaths reported globally in 2021. Despite the increasing prevention and control measures driven by the World Health Organization (WHO), nearly half of the population is still at risk of malaria, with a reported increase in the incidence of imported malaria in European countries. To this end, implementing large-scale, high-coverage, early diagnosis, and accurate prognosis of severe malaria is critical to reducing the impact of malaria in Europe. Due to its high sensitivity, parasite counting by microscopy observation is the current gold standard method. However, it is inappropriate for its application at the point of care (PoC). The rapid diagnostic tests (RDTs) based on lateral flow assay are the best option for PoC testing since they accomplish the REASSURED criteria WHO recommends. However, this method doesn't provide quantitative prognostic information and has proved low clinical sensitivity with low parasitemia samples (asymptomatic parasite carriers). With this aim, I propose for the first time the development of a smartphone-powered electrophoretic-driven aptamer paper-based LFA capable of providing a quantitative measurement of 2 parasite (PfHRP2, pan-pLDH) and 2 host (ang-2 and CRP) malaria biomarkers within minutes. Compared to capillarity-driven LFA, the flow control by electrophoresis enables the application of different synergic strategies to increase assay sensitivity, such as integrated incubation steps and purification of interfering biomolecules. Highly specific aptamers will be developed by a fast and cost-effective microfluidic selection approach, used as bioreceptors with stability for electrokinetics. This will enable an early diagnosis and an accurate prognosis of malaria, reducing the risk of developing severe symptoms. Upon successfully validating the device in non-endemic areas (host institution), I expect its use in low-resource, malaria-endemic areas.

Keywords: malaria,diagnosis,prognosis,electrokinetic,lateral flow assay,aptamers
Understanding yeasts and lactic acid bacteria interactions to develop a mixed culture bioprocess for the production of ethanol from food waste (Waste2Ethanol)

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: Environment and Geosciences
Countries involved: Belgium,Germany
Call: MSCA Postdoctoral Fellowships 2023 (HORIZON-MSCA-2023-PF-01, 2023)
Start date: 2025-01-01
End date: 2026-12-31
Duration (months): 24.0
Total project cost (EUR): 175920.0
EU funding (EUR): 175920.0
Participants: 2
Project status: SIGNED

The EU Commission’s bioeconomy strategy aims at shifting the European economy towards a greater and more sustainable use of renewable resources, where waste streams are converted into value-added products. Ethanol is a platform chemical and fuel with a global production of 102 billion liters per year. However, its production requires sugar crops, leading to conflicts over land use and potentially contributing to food shortages or increased food prices. Current feedstock alternatives (lignocellulosic materials or algae biomass) require complex pre-treatments, resulting in higher production costs that limit their application. Waste2Ethanol aims to develop a novel non-sterile bioprocess without any pretreatments for the production of ethanol from food waste. For this, our understanding of the metabolic interactions between yeasts (ethanol producers) and carbohydrate fermenting bacteria needs to be expanded. In Waste2Ethanol, this will be done with a combination of mixed culture biotechnology methods, defined microbial co-cultures and cutting-edge molecular and microscopy techniques. Hosted at UGent, I will study the competition and synergies of yeasts and carbohydrate fermenting bacteria with microbial enrichment cultures and bioinformatics techniques to identify selective conditions that would favor the production of ethanol. During the secondment at Osnabrück University, I will gain complementary skills in the use of defined microbial co-cultures and advanced microscopy techniques to study metabolic interactions. This unique combination of expertise will significantly improve my career perspectives towards my ambition to establish my own research group at the intersection of microbial ecology and non-axenic biotechnology. Overall, the generated knowledge will allow to steer a microbial community towards ethanol production and pave the road to a non-sterile bioprocess for the production of ethanol from food waste at higher TRLs.

Keywords: ethanol,food waste,mixed culture biotechnology,microbial enrichment cultures,defined microbial co cultures