Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
ENDING COVID 19 VARIANTS OF CONCERN THROUGH COHORT STUDIES: END-VOC (END-VOC)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Health
Theme: Health
Destination: Other health destinations
Action type: Research and Innovation actions
Countries involved: United Kingdom,Italy,Germany,Spain,Norway,Netherlands,Nigeria,Switzerland,India,Luxembourg,Pakistan,Mozambique,Philippines,Brazil,Palestine, State of,Portugal,United States,Uganda
Call: Cohorts united against COVID-19 variants of concern (HORIZON-HLTH-2021-CORONA-01, 2021)
Start date: 2022-05-01
End date: 2025-10-31
Duration (months): 42.0
Total project cost (EUR): 10496136.5
EU funding (EUR): 10496136.5
Participants: 26
Project status: SIGNED

The END-VOC consortium will support the European and global response to the COVID-19 pandemic and Variants of Concern (VOC) through well characterised cohorts and linked with existing European and international initiatives. END-VOC consists of 19 partners in Europe (UK, Spain, Italy, Germany, Netherlands, Norway, Italy), South America (Brazil and Peru), Africa (Mozambique, South Africa, Nigeria and 13 ANTICOV African countries), Middle East (Palestine) and Asia (India, Pakistan, Philippines) with a focus on countries affected by VOCs and VOIs. We will elucidate the global circulation of the current and emerging SARS-CoV-2 VOCs and their characteristics, including transmissibility, pathogenicity and propensity to cause reinfection, to support best control strategies and the development of diagnostics; evaluate the impact of VOCs on the effectiveness of different vaccines and vaccination strategies; and assess the implications of VOCs on the choice of optimal treatment options. END-VOC will also investigate how VOCs alter long-term post-infection sequelae and where new VOCs emerge within hosts using our clinical cohorts. We will inform future preparedness and response working closely with international and national public health organisations and existing cohort consortia. Specific beyond state-of-the-art components of END-VOC include the use of novel phylogenetic prediction tools and mathematical modelling; generation of powerful cohorts through sentinel surveillance in low and middle income settings and cohorts of travellers to increase our global reach; use of novel predictive modelling of clinical outcomes by VOC and comorbidity/treatment and evaluation of differences in natural and vaccine immunity by VOC; antiviral screening models within cohorts and an artificial intelligence driven tool for the prediction of long COVID.

Keywords: cohorts severe acute respiratory syndrome coronavirus 2 covid 19 deletions vaccination treatment variant of concern variant of interest mutations genomics phylogenetics modelling
Pre-commercialization of new generation Atomic-layer-deposited Lasers for future green high-performance data centers (A-Laser)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Proof of concept grants
Action type: ERC actions
Countries involved: Finland
Call: ERC PROOF OF CONCEPT GRANTS2 (ERC-2022-POC2, 2022)
Start date: 2023-01-01
End date: 2024-06-30
Duration (months): 18.0
Total project cost (EUR): 150000.0
EU funding (EUR): 150000.0
Participants: 1
Project status: CLOSED

The continuous growth of global data traffic pushes the data center technology boundaries and their energy consumption. Data centers already use more than 2% of the global electricity and are expected to consume 20% by 2025. The new generation hyperscale data centers offer a more energy-efficient alternative to conventional data centers but are limited by the current technology restrictions. Silicon photonics has been deemed to solve current bottlenecks for building green hyperscale data centers. However, this technology is challenged by the complicated and expensive fabrication methods of the laser sources, which represent 40% cost of the entire silicon transceiver market. Using a simple fabrication method invented in our ERC Advanced project, we have designed a waveguide light source that can be fabricated onto the silicon-integrated platform with a single-step, straightforward, low-cost, low-temperature and scalable process that lowers the fabrication cost ~10 times compared to the state-of-the-art light sources. Such technologic breakthrough will push the implementation of silicon photonics in hyperscale data centers, allowing them to maintain a low energy footprint while meeting the ever-increasing bandwidth requirements of the growing big data societal challenge. Our project aims to further develop the novel technology and demonstrate its effectiveness for data center applications, to create the first-of-its-kind low-cost and scalable fabrication technology for the silicon photonics market, compatible with the current systems used in the industry. Furthermore, we will prepare and validate the business concept with value chain players, strengthen our IPR strategy, and prepare the commercialization to establish a start-up aiming at serving this significantly growing market (40% Compound Annual Growth Rate).
Breakthrough industry grade tagging of plastic products (BIGTOP)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Proof of concept grants
Action type: ERC actions
Countries involved: Belgium
Call: ERC PROOF OF CONCEPT GRANTS (ERC-2025-POC, 2025)
Start date: 2026-01-01
End date: 2027-06-30
Duration (months): 18.0
Total project cost (EUR): 150000.0
EU funding (EUR): 150000.0
Participants: 1
Project status: SIGNED

BIGTOP aims to bring a groundbreaking molecular tagging technology for plastic materials closer to the market by making use of sequence-defined oligomers developed under the ERC advanced grant CiMaC project. These molecular tags, which encode information using precise monomer sequences, offer a powerful solution for product traceability, anti-counterfeiting, and origin identification across industries. Thanks to the research in CiMaC, we have already demonstrated the scalable synthesis and high temperature stability of these sequence-defined oligomers, bridging the gap between academic innovation and industrial feasibility. BIGTOP will focus on remaining critical challenges such as ensuring that these tags maintain their integrity throughout real-world manufacturing processes, including high-temperature extrusion and curing. Our patent-protected research confirms that oligoamides meet such demands, offering exceptional thermal and mechanical stability when directly incorporated into materials. In practice, this technology enables fast and simple initial detection via UV or fluorescence spectroscopy, followed by highly specific molecular identification using tandem mass spectrometry techniques. This combination of tag robustness, simplicity of use and precision multi-level detection, offers a unique technological innovation for industrial grade tagging of plastics. The growing regulatory pressure around material provenance and sustainability claims, alongside concerns with regard to counterfeiting in high-value supply chains, underpins the demand for this type of robust molecular tags. BIGTOP will validate that the tagging concept is compatible with large-scale production processes, identify the most promising market segments, and finally develop a valorization strategy. To ensure success, the project will combine insights from polymer chemistry, manufacturing scale-up and business development, positioning the technology for successful uptake by industry.
DIgital LAser PROduction: Digital Twins of Laser Processing for Multi-Capability Manufacturing of Complex Components and Certification (DILAPRO)

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: Photonics (co-programmed)
Countries involved: Denmark,Belgium,Ireland,Norway,Spain,Switzerland,Italy,Germany
Call: High-precision OR complex product manufacturing – potentially including the use of photonics (Made in Europe and Photonics Partnerships) (IA) (HORIZON-CL4-2023-TWIN-TRANSITION-01, 2023)
Start date: 2024-01-01
End date: 2026-12-31
Duration (months): 36.0
Total project cost (EUR): 6424934.94
EU funding (EUR): 5815700.07
Participants: 13
Project status: SIGNED

Making Europe the first digitally led circular, climate-neutral and sustainable economy needs major changes across manufacturing: efficiencies in energy and material consumption, new solutions to problems in certification and standardisation, and upskilling of the European workforce. DILAPRO contributes to all of these, driving decarbonisation and the twin Green and Digital Transitions via two ground-breaking software tools for laser-based production of complex products. DILAFACT (Digital Laser Factory) is a sustainable and scalable platform for laser process planning via Digital Twins of laser-material interactions, including additive, subtractive, and thermal processes. DILACERT (Digital Laser Certification) tackles a major hurdle in rapidly-developing laser and additive manufacturing technologies: certification and standardisation. In the short DILACERT enables end users to easily process production data for certification; in the long term it paves the way for remote semiautomated digital certification of produced parts, a major paradigm shift in complex part production. DILAPRO grounds its development in specific materials (316L, IN718, IN625) and laser technologies (PBF-LB, DED-LB, and Laser Texturing) as deployed on 6 operational production lines owned by project partners. These will be developed as distinct modules during the first half of the project, and synthesised into DILAFACT and DILACERT in the project’s second half. To ensure the competitiveness and sustainability of European manufacturing in the long term, other developers and end-users will be able to contribute modules to both software, kick-started by DILAPRO’s living communities and innovative IP plan covering both commercial and OA licenses. DILAPRO offers two scalable, sustainability-focused solutions for the European laser-based, high-precision manufacturing industry, and will thus not simply develop a single one-off product, but a resilient force-multiplier for the long term.

Keywords: laser processing,digital twins,multi capability manufacturing,complex components,certification
Judges’ Off-Bench Activities: Evidence and Theory on Judicial Politics from Africa. (Off-Bench)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: Institutions, Governance and Legal Systems
Panel description: Political science, international relations, law
Countries involved: United Kingdom,Zambia,Kenya
Call: ERC ADVANCED GRANTS (ERC-2024-ADG, 2024)
Start date: 2026-02-01
End date: 2031-01-31
Duration (months): 60.0
Total project cost (EUR): 2264067.86
EU funding (EUR): 2221791.0
Participants: 4
Project status: SIGNED

Off-Bench adopts an innovative approach to the study of judges and judicial politics. Rather than focusing on judicial rulings (the mainstay of academic study) it undertakes the first systematic study of what judges do outside of their courtrooms as part of their official duties and public engagements (hereon off-bench activities), why, and with what impact. This politics project adopts this approach for five reasons: off-bench activities are inherently political; judges engage in a wider range of off-bench activities than has hitherto been recognised; what judges do off-bench is highly revealing of their role understandings; what judges do off-bench matters for the roles that they play both on and off the bench; and judges are critical political actors who can help to promote or undermine the rule of law, accountability, and human rights. The project focuses on contemporary Africa as a most likely case for such off-bench significance and to build theory from the Global South. To facilitate the complex mix of qualitative and quantitative research required to map and then analyse off-bench activities the project will undertake extensive research in two countries. Kenya and Zambia are selected as most similar cases that display different levels of off-bench activism and judicial independence. To test theory developed and evaluate the broader applicability of findings the project will conduct additional research in five ancillary cases – Ghana, Rwanda, Senegal, South Africa, and Uganda – selected for differences in levels of authoritarianism, conflict, and off-bench activities, and common and civil law traditions. This ambitious project will transform how we study and understand the political role, strategies, and significance of this critical democratic actor and make ground-breaking contributions to our understanding of African politics, institutional theory, and role of performance in politics and inform and enhance judicial reform and democracy support efforts.

Keywords: judges judicial politics african politics democratisation hybrid regimes
ELECTROCHEMICAL DNA-BASED SENSORS FOR IMMUNOTHERAPY MONITORING (IMMUNO-MONITORING)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Proof of concept grants
Action type: ERC actions
Countries involved: Italy
Call: ERC PROOF OF CONCEPT GRANTS1 (ERC-2022-POC1, 2022)
Start date: 2022-06-01
End date: 2023-11-30
Duration (months): 18.0
Total project cost (EUR): 150000.0
EU funding (EUR): 150000.0
Participants: 1
Project status: CLOSED

During the initial part of the ERC-Consolidator Grant PRO-TOOLKITS we have successfully demonstrated a novel approach for antibodies detection. The platform uses antigen-conjugated synthetic DNA strand to achieve the rapid and inexpensive detection of target antibodies. Our platform offers several advantages (low-cost, single-step, rapid) in comparison of other methods for antibody detection and is so versatile that can be used also for the detection of Bispecific Antibodies (BsAb). On the basis of interactions with pharmaceutical companies and following a market analysis we have found that there is a growing need for similar approaches that can allow to monitor the efficacy of immunotherapies. This is especially true for immunotherapies using BsAb as there are no standard analytical methods for these targets. Given these considerations, the goal of this project is to evaluate the commercial potential of our innovative platform for immunotherapy efficacy monitoring with particular focus on the detection and characterization of BsAb. During the project we will 1) Fully characterize the DNA-based antibody sensor for the detection of a model BsAb (Anti EGFR/Anti HER2 BsAb) in terms of analytical performances (i.e. sensitivity, specificity, stability etc.) with direct comparison with other used techniques; 2) Prepare a Manufacturing Plan for producing/testing the Ab-switch; 3) Establish an IP strategy for patent filing and maintenance; 4) Determine a business and commercialization planning.
Smart E-skins for Life-like Soft Robot Perception (SELECT)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Systems and Communication Engineering
Panel description: Electrical, electronic, communication, optical and systems engineering
Countries involved: United Kingdom
Call: ERC STARTING GRANTS (ERC-2024-STG, 2024)
Start date: 2024-09-01
End date: 2029-08-31
Duration (months): 60.0
Total project cost (EUR): 1486463.0
EU funding (EUR): 1486463.0
Participants: 1
Project status: SIGNED

Nature, through millennia of evolution, has endowed living organisms with unmatched sensory adaptability. As robotics weave more deeply into the fabric of human society, a compelling challenge emerges: mimicking the sensory intelligence intrinsic to these life forms. The intricate synergy between the organism’s skin and brain, delivering unrivalled sensory insight and data interpretation, epitomises a domain in robotics still uncharted. Cultivating such perceptive sense in robots is crucial; it heralds a future with enhanced safety and adaptability in human-robot interactions, revealing new horizons for innovative applications. SELECT aims to bridge this perception gap in soft robotics – a rapidly evolving robotic field inspired by the softness of living beings. At the heart of SELECT lies the ambition to pioneer smart electronic skins (e-skins) that resonate with the sensory capability of organisms. SELECT's objectives include: 1. Develop multi-modal e-skins for holistic perception. 2. Build models to simulate the integration of e-skins and robots. 3. Explore automated, adaptive e-skin designs. 4. Advance learning algorithms to decode e-skin data. 5. Streamline e-skin deployment and training. SELECT's outcomes promise to redefine soft robot perception, synergising e-skin sensory attributes with state-of-the-art machine learning. Beyond advancing robotics, SELECT envisions reshaping our interaction dynamics with intelligent systems, championing a new epoch of human-machine symbiosis.

Keywords: soft robotics,perception
ADAPTIVE TRANSPORT SYSTEMS WITH HOLISTIC REPRESENTATION OF SUPPLY AND DEMAND (ADAPT-OR)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Human Mobility, Environment, and Space
Panel description: Human geography, demography, health, susta inability science, territorial planning, spatial analysis
Countries involved: Netherlands
Call: ERC STARTING GRANTS (ERC-2023-STG, 2023)
Start date: 2024-01-01
End date: 2028-12-31
Duration (months): 60.0
Total project cost (EUR): 1499999.0
EU funding (EUR): 1499999.0
Participants: 1
Project status: SIGNED

Transport systems are complex with various entities across different decision-making levels. There is currently no comprehensive way to model these entities and their interactions, which prevents utilizing the full potential of the system. For efficient and sustainable transportation, we need to model the perspective of both the supply (e.g., services, infrastructure) and the demand side (e.g., preferences of users). Only then a holistic modelling framework can be developed where the decisions at different levels learn from one another and are adapted continuously in a robust way while accommodating the different preferences. I propose a holistic adaptive modelling framework that considers the interaction between different levels, both on the supply and demand sides, in order to adapt the decisions towards increased efficiency and sustainability. This necessitates a paradigm change in modelling as it is challenging to maintain robustness across different time-scales at the network level. Even though integrated models for multiple decision-making levels (strategic, tactical, operational) are a trend, they only allow a reactive ex-post assessment but are not dynamically coupled (not self-learning). I plan to achieve this by developing model-based adaptive optimization and learning methods with my expertise on optimization and behavioural modelling. For example, based on the performance of the routing decisions at the operational level in terms of delays, the decisions on fleet sizing and/or capacity of facilities will be adapted. Similarly, based on a continuous learning of the preferences of users, transport decisions will be adapted. ADAPT-OR will lead to new models and algorithms for transportation researchers (and beyond) with self-learning capabilities. This capability will enable service providers to adapt and maintain their business, users to receive better services and society to reach sustainable transport solutions addressing one of EU’s grand challenges.

Keywords: adaptive transportation,behavioral models,optimization,supply demand interactions
The hidden majority: high-resolution imaging and genomics of the most ecologically important microbial eukaryotes in the ocean (IMAGEN3D)

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: Spain
Call: MSCA Postdoctoral Fellowships 2022 (HORIZON-MSCA-2022-PF-01, 2022)
Start date: 2024-09-01
End date: 2026-08-31
Duration (months): 24.0
Total project cost (EUR): 181152.96
EU funding (EUR): 181152.96
Participants: 1
Project status: SIGNED

How have eukaryotes evolved into the vast diversity we see nowadays? At present this simple question remains a mystery, mostly due to the vast uncharted microbial environmental diversity recurrently unveiled by molecular surveys. This gap in knowledge hinders a deep understanding of basic eukaryotic diversity, evolution and biology, and creates a biased perception towards well-characterized organisms of human interest. Yet, since the beginning of microbial research, from Leeuwenhoek and Haeckel, unicellular eukaryotes have been largely studied by optical methods, describing an extensive variety of shapes and morphologies. We therefore need new and different approaches to explore unknown eukaryote diversity. The goal of this project is to better understand early and enigmatic eukaryotic evolution by studying the morphology and genomes of the most informative undescribed eukaryotic lineages. Studies of novel eukaryotic diversity have historically relied on arbitrary factors regardless of their environmental abundance due to the lack of data. Yet, abundant groups are the most practical to explore. I will first identify the most environmentally abundant species that are distantly related to morphologically described groups. Next, I will develop a novel approach that allows the acquisition of 3D morphological data by imaging group-specific fluorescence in situ hybridization probes in combination with a set of fluorescent dyes labeling relevant subcellular features. Finally, I will sequence and assemble their genomes to better resolve the eukaryotic tree of life, by filling out poorly represented lineages that are distantly related to well-characterized species. This project will bring for the first time the link between already available environmental short sequences and their organismal morphology and genomic data.

Keywords: protists,molecular diversity,evolution,single cell genomics,characterization,in situ hybridization,3d fluorescence microscopy