Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Early Giants in Context: How could Galaxies Grow so Rapidly in the First Billion Years? (FIRST-GIANTS)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Universe Sciences
Panel description: Astro -physics/ -chemistry/ -biology; solar system; planetary systems; stellar, galactic and extragalactic astronomy; cosmology; space sciences; astronomical instrumentation and data
Countries involved: Germany
Call: ERC STARTING GRANTS (ERC-2025-STG, 2025)
Start date: 2026-07-01
End date: 2031-06-30
Duration (months): 60.0
Total project cost (EUR): 1498750.0
EU funding (EUR): 1498750.0
Participants: 1
Project status: SIGNED

The James Webb Space Telescope (JWST) has revealed that galaxies in the first billion years of the Universe are maturing surprisingly fast. Massive galaxies outnumber predictions, appear to have high stellar mass densities, host massive black holes and in some cases disky morphologies. Understanding this rapid assembly is crucial: the abundance of early massive galaxies would pose a major challenge for current galaxy formation models in the ΛCDM framework. However, these results remain contentious, as they are primarily based on broad-band photometric samples, interpreted with stellar population models that were calibrated in the local Universe. The masses, nature and space density of the candidate massive galaxies therefore are highly uncertain. To determine how galaxies could grow so rapidly requires a comprehensive approach: high-quality spectra for a large set of candidate massive galaxies, combined with novel modelling to obtain dynamical masses, robust stellar masses and star formation histories, and to identify active galactic nuclei (AGN). As PI of a large ongoing spectroscopic JWST program, I have obtained the first spectra that reveal early massive galaxies in unprecedented detail, along with a broader ‘context sample’ of several thousand galaxies. I have developed the necessary kinematic modelling tools to get dynamical masses of early galaxies, and have tailored stellar population models in place. We will robustly constrain the abundance of massive galaxies in the first billion years, their masses, structures and star formation histories, and AGN duty cycle. We will embed these results in the context of cosmological galaxy formation models. We can then determine how galaxy assembly took place in dark matter haloes, constrain the star formation efficiency, and answer how star formation was regulated in early galaxies. This proposal presents a breakthrough in our understanding of the first billion years, setting a new benchmark for galaxy formation models.

Keywords: high redshift galaxies galaxy formation galaxy dynamics galaxy stellar populations
Unified Modeling and Automated Scheduling for Manufacturing as a Service (UniMaaS)

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: Research and Innovation actions
Partnership: Made in Europe (co-programmed)
Countries involved: Greece,United Kingdom,Belgium,France,Germany,Spain,Luxembourg,Canada,Poland,Italy
Call: Manufacturing as a Service: Technologies for customised, flexible, and decentralised production on demand (Made in Europe Partnership) (RIA) (HORIZON-CL4-2024-TWIN-TRANSITION-01, 2024)
Start date: 2025-01-01
End date: 2027-12-31
Duration (months): 36.0
Total project cost (EUR): 7520869.53
EU funding (EUR): 6483593.82
Participants: 18
Project status: SIGNED

Manufacturing in Europe should urgently address the following challenges towards the adoption of the Manufacturing as a Service paradigm: product customisation, circularity and sustainability, minimal downtime, predictive maintenance, seamless communication, reliability and robustness to uncertainties in demand and variability of resources, and cost reduction and performance optimisation. Unified Modeling and Automated Scheduling for Manufacturing as a Service (UniMaaS) project will develop a platform with a set of advanced technologies for offering flexible and decentralized manufacturing resources and supply chains as a Service to European SMEs and Industries. To realize this vision, the proposed platform will deploy 3 integrated Suites: (i) Data Modelling Suite: offering manufacturing dataspaces, cloud-based resource monitoring, trusted cross-company data exchange and digital product passport, (ii) Modelling Suite: offering modular modeling of manufacturing resources, intent-based servitization , AI-based estimations and Zero-X analysis, and (iii) Decision-Making Suite: offering scheduling and planning of manufacturing resources, circularity and sustainability optimization. The platform will adopt advanced digital technologies such as cloud computing, digital twins and trustworthy AI, as key enablers towards fulfilling its objectives. UniMaaS platform will provide easy access to customized manufacturing service chain and will support the entire life-cycle management of processes and products. The UniMaaS Suites and the Platform will be demonstrated in 4 Pilots including aircraft maintenance, automotive seating, 3D construction printing and logistics/warehouse management.

Keywords: manufacturing data spaces,digital product passport,hybrid systems,control theory,circularity and sustainability,cloud manufacturing,digital twins
MOde LOcKing for Advanced Sensing and Imaging) (MOLOKAI)

Framework: Horizon Europe — Innovative Europe
Programme: The European Innovation Council (EIC)
Theme: EIC Transition
Destination: Open to supporting projects in all areas of science, technology,...
Action type: EIC actions
Countries involved: Belgium,Netherlands,Denmark,Germany
Call: EIC Transition Open 2023 (HORIZON-EIC-2023-TRANSITION-01, 2023)
Start date: 2024-08-01
End date: 2027-07-31
Duration (months): 36.0
Total project cost (EUR): 2522500.0
EU funding (EUR): 2522500.0
Participants: 4
Project status: SIGNED

The optical frequency comb is a spectrum of evenly spaced narrow laser lines. Optical frequency combs have revolutionized time and frequency metrology by linking microwave and optical frequencies. However, realizing their full potential in a broader range of applications such as 3D imaging, environmental sensing, LIDAR, and high-speed optical communications, is conditioned by the availability of inexpensive highly miniaturized devices. Progress in integrated optics towards chip-scale frequency combs has made significant strides in recent years. UGent has been at the forefront of this evolution. It has developed unique technologies in heterogeneous integration, enabling the long-missing functionality of optical gain on a chip. This unlocks the full integration of combs, in particular, in the infrared, but also in the near-infrared range (800-1100 nm), the key to sensing in water-dominated media as encountered in biological samples, e.g., in optical coherence tomography setting, food industry, and environmental sensing. In MOLOKAI UGent will engage in a close collaboration with the group at MBI which is the pioneer of the applications of frequency combs applied to dual-comb interferometry and, in particular, the initiator of the extension of frequency-comb techniques to 3D imaging, and to Raman spectroscopy. In this way in MOLOKAI, we aim to leverage the latest breakthroughs in chip-scale frequency-comb technology to transition these technologies in a real-life setting. MOLOKAI will work further on our initial dual-comb results to make a broadband on-chip interferometer. For that, MOLOKAI will collaborate closely with IBSEN Photonics, a spectrometer company, to make high-resolution spectrometers that can be used to read out Bragg sensors in fibers. Next, the dual-comb technology will be ported to a GaAs-on-silicon nitride platform. Here dual-comb systems allow for the prospect of high-resolution images.

Keywords: combs,heterogenuous integration
Dual screening by Spectral Artificial Visual Examination (SAVE) for Female Genital Schistosomiasis (FGS) and cervical cancer. Digital, new, low-cost, and simple screening and training. (DUALSAVE-FGS)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Health
Theme: Health
Destination: Tackling diseases and reducing disease burden
Action type: Research and Innovation actions
Countries involved: Norway,Greece,South Africa,Eswatini,Denmark,Mozambique
Call: Innovative approaches to enhance poverty-related diseases research in sub-Saharan Africa (HORIZON-HLTH-2021-DISEASE-04, 2021)
Start date: 2022-08-01
End date: 2026-07-31
Duration (months): 48.0
Total project cost (EUR): 7984443.75
EU funding (EUR): 7984441.0
Participants: 9
Project status: SIGNED

Around 300 million African girls and women are at risk of the poverty related disease, Female Genital Schistosomiasis (FGS), and 400 million are at risk for cervical cancer. Most of these are in Sub-Saharan Africa. FGS may be mistaken for cervical cancer or a sexually transmitted infection, and treated accordingly. Women may have FGS lesions, have cryptogenic bloody or malodorous discharge, or pain, and, be at higher risk for HIV and Human papillomavirus (HPV). FGS is best diagnosed by point-of-care visualisation of the shape and colour of the lesions. However, health professionals require several weeks of training where the disease is seen frequently, and often they need a colposcope to recognise FGS. Worldwide, there are only a handful of health professionals who are proficient in FGS diagnosis. A multispectral highly innovative colposcope linked to a smartphone, designed by an SME for cervical cancer recognition, will be adapted and validated for FGS diagnosis in this proposal. In three countries with different FGS epidemiology and different practices for gynaecological investigations of women, we will conduct a clinical trial in the spirit of the EDCTP agenda, with the ultimate aim of a patent and local production. With lessons from the SARS-CoV-2 pandemic, an eLearning course will be designed and trialled. Equipment, consultations and training will be adapted to practical realities (cultures, unstable electricity/internet, poverty, vulnerability). As recommended by the WHO and the "HPV faster approach", the diagnosis should be at the point-of-care. Management and data collection protocols will be designed in collaboration with the national health authorities in Southern Africa, the WHO and also in one European country. This is a thrust to promote clinical research and digitalisation for vulnerable populations. Hundreds of clinicians and scientists will receive training in FGS, clinical trials, and social sciences.

Keywords: screening,diagnosis,training of health professionals,scale up,female genital schistosomiasis
Extreme and Sustainable Graph Processing for Urgent Societal Challenges in Europe (Graph-Massivizer)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Digital, Industry and Space
Theme: Digital
Destination: World-leading Data and Computing Technologies
Action type: Research and Innovation actions
Countries involved: Austria,Italy,Ireland,Slovenia,Norway,Netherlands,Germany,Spain
Call: Extreme data mining, aggregation and analytics technologies and solutions (RIA) (HORIZON-CL4-2022-DATA-01, 2022)
Start date: 2023-01-01
End date: 2025-12-31
Duration (months): 36.0
Total project cost (EUR): 4998062.5
EU funding (EUR): 4998062.5
Participants: 13
Project status: SIGNED

Graph-Massivizer researches and develops a high-performance, scalable, and sustainable platform for information processing and reasoning based on the massive graph representation of extreme data. It delivers a toolkit of five open-source software tools and FAIR graph datasets covering the sustainable lifecycle of processing extreme data as massive graphs. The tools focus on holistic usability (from extreme data ingestion and massive graph creation), automated intelligence (through analytics and reasoning), performance modelling, and environmental sustainability tradeoffs, supported by credible data-driven evidence across the computing continuum. The automated operation based on the emerging serverless computing paradigm supports experienced and novice stakeholders from a broad group of large and small organisations to capitalise on extreme data through massive graph programming and processing. Graph Massivizer validates its innovation on four complementary use cases considering their extreme data properties and coverage of the three sustainability pillars (economy, society, and environment): sustainable green finance, global environment protection foresight, green AI for the sustainable automotive industry, and data centre digital twin for exascale computing. Graph Massivizer promises 70% more efficient analytics than AliGraph, and 30% improved energy awareness for ETL storage operations than Amazon Redshift. Furthermore, it aims to demonstrate a possible two-fold improvement in data centre energy efficiency and over 25% lower GHG emissions for basic graph operations. Graph-Massivizer gathers an interdisciplinary group of twelve partners from eight countries, covering four academic universities, two applied research centres, one HPC centre, two SMEs and two large enterprises. It leverages the world-leading roles of European researchers in graph processing and serverless computing and uses leadership-class European infrastructure in the computing continuum.

Keywords: extreme data,massive graphs,sustainability,serverless computing,computing continuum,green finance,global foresight,green automotive,sustainable exascale computing
Politics of humanitarian care: aid, displacement and social reproduction in Croatia (REHUM)

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: Social Sciences and Humanities
Countries involved: Germany,Hungary
Call: MSCA Postdoctoral Fellowships 2023 (HORIZON-MSCA-2023-PF-01, 2023)
Start date: 2025-09-01
End date: 2027-08-31
Duration (months): 24.0
Total project cost (EUR): 189687.36
EU funding (EUR): 189687.36
Participants: 2
Project status: SIGNED

The idea behind the REHUM project is that institutionalized practices of care are being replaced by emergency humanitarian aid, forming an ambivalent concept of humanitarian care. By using a participative ethnographic approach in two humanitarian settings – post-earthquake displacement and irregularized migration – the project will explore how and if the expansion of humanitarian initiatives in different emergencies points to the same problem of the erosion of institutionalized care while shedding light on ambivalent transformations of grassroots organizations and its employees/volunteers in their attempts to replace such systems. While previous research pointed out different aspects of social inequalities enhanced in and by humanitarian programs, the emphasis on the entanglements between humanitarianism and care in the context of migration/displacement in Croatia, especially regarding the phenomenon that political theorist Nancy Fraser termed “crisis of care”, has not been quite touched upon. In order to expand the critique of humanitarian care in Croatia, but also in a wider sense of the European (semi)peripheries, REHUM will theoretically and empirically explore the intersection between social reproduction, humanitarianism, and displacement. Starting from the assumption that care, understood as an essential part of life and a practice inevitable for human development, is structurally devalued and externalized to the area of household and informal aid initiatives, REHUM will aim to identify the ways in which humanitarianism in Croatia underpins that process while situating scarce state responses and their replacement with temporary humanitarian solutions in a broader political framework.

Keywords: humanitarianism,care,social reproduction,displacement,aid
Akara Violet Robotic Infection Control System (AVRICS)

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: Ireland
Call: EIC Accelerator Open 2021 (HORIZON-EIC-2021-ACCELERATOROPEN-01, 2021)
Start date: 2022-04-01
End date: 2025-04-30
Duration (months): 37.0
Total project cost (EUR): 3500983.75
EU funding (EUR): 2450688.63
Participants: 1
Project status: CLOSED

Akara is a spin-out from one of Europe’s leading robotics labs at Trinity College Dublin. The founders collectively boast more than 40 years’ experience developing and deploying some of the most advanced robotic systems ever built to support front-line workers in the healthcare industry; last year one solution was featured on the cover of Time magazine, a first for a European company. Akara offers ‘Violet’, an AI-powered autonomous robot equipped with UV light – a scientifically proven germ-killer - for disinfection of hospitals, nursing homes and potentially endless other areas where harmful germs reside. ‘Violet’ has been extensively tested in real clinical settings resulting in: 3X more effective at killing germs; 2-4X less time to disinfect rooms than the current approach. Violet is the only UV robot designed to be safe for use around people; this overcomes fundamental limitations of state-of-the-art disinfection technology, which require rooms to be evacuated before and during use.

Keywords: healthcare associated infections,intensive care units,automated cleaning,machine learning,artificial intelligence,uv disinfection
Valence asymmetries: the positive, the negative, the good and the bad in language, mind and morality (Valence Asymmetries)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: The Human Mind and Its Compl exity
Panel description: Cognitive science, psychology, linguistics
Countries involved: Spain
Call: ERC ADVANCED GRANTS (ERC-2023-ADG, 2023)
Start date: 2024-08-01
End date: 2029-07-31
Duration (months): 60.0
Total project cost (EUR): 2096875.0
EU funding (EUR): 2096875.0
Participants: 1
Project status: SIGNED

An asymmetric behavior between the positive and the negative has been evidenced in psychology, for information processing, attention, recognition and decision making, in philosophy, for judgments about morality and intentionality, and in linguistics, for a range of lexical, syntactic, semantic and pragmatic phenomena. Negative information grabs our attention, we process it more carefully, we recall it with greater precision. We easily blame others for the negative side-effects of their actions, but do not praise them for the positive ones. It takes many nice words to overthrow one nasty remark. When we say that something is "not good", we usually imply that it is bad, but by saying "not bad" we do not imply that it is good. Valence asymmetries have arisen on many horizons but have seldom been brought into correspondence, and are at odds with most theories of value. The present project is a pioneering attempt to secure the premises for a cross-fertilization between the different accounts of valence asymmetries. It will deploy methods from philosophy (argumentation and conceptual analysis), formal semantic and value-theoretic models, and experimental methodology from psycholinguistics and moral psychology. It has three main objectives: - highlight the fundamental role that valence plays beyond emotion, in particular, in value judgments and language; - examine what the different asymmetries have in common, and whether they call for a unified explanation; - show that valence asymmetries are not necessarily irrational, but often derive from a fundamental asymmetry between positive and negative value, and, as such, are a key component of our cognitive and linguistic architecture. Furthermore, we will (a) articulate the relationship among the notions of valence, value and polarity; (b) put forward a novel account of the asymmetry of negation; (c) unearth new asymmetries in the realm of morality, virtue and vice; and (d) provide an account of valence reversals.

Keywords: evaluative language affective meaning value judgments positive and negative valence semantics of antonyms polarity moral theory
Decoding epistatic genome/RNome interactions in eukaryotic fitness gain using Leishmania parasites as a unique model system (DECOLeishRN)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Synergy grants
Action type: ERC actions
Countries involved: France,Israel
Call: ERC Synergy Grants (ERC-2022-SYG, 2022)
Start date: 2023-05-01
End date: 2029-04-30
Duration (months): 72.0
Total project cost (EUR): 8620835.0
EU funding (EUR): 8620835.0
Participants: 3
Project status: SIGNED

Darwinian evolution plays a central yet poorly understood role in human disease. Iterations between genetic mutation and environmental selection drive cancer development, microbial infection and therapeutic failure, thus increasing human mortality. The molecular mechanisms that harness the deleterious effects of genome instability to generate beneficial phenotypes in these pathogenic systems are unknown. Here we investigate this important unsolved question in the protozoan parasite Leishmania that causes devastating human infections. In the absence of transcriptional regulation, these early-branching eukaryotes exploit genome instability to regulate expression by gene dosage. Leishmania thus represents an ideal system to investigate how genome instability drives fitness gain in fast evolving, eukaryotic cells, such as observed during cancer development. Synergizing our expertise in genomics, evolution, systems and RNA biology, we have recently made several breakthrough discoveries that link parasite fitness gain to epistatic interactions between co-amplifying genes of small, non-coding RNAs, which program epitranscriptomic and translational regulation. We hypothesize that these genome/RNome interactions generate the phenotypic landscape underlying Leishmania fitness gain. Our proposal investigates this ground-breaking concept through two Specific Aims that (i) combine experimental parasite differentiation and evolution in vitro and in vivo to reveal molecular mechanisms underlying Leishmania predictive adaptation and fitness gain, and (ii) investigate how RNA modification and non-coding RNAs contribute to adaptation by regulating mRNA stability and translational control. Our findings will be highly relevant to other fast growing, eukaryotic systems that rely on genome instability, such as cancer or fungal pathogens.

Keywords: eukaryotic fitness gain,genome instability,leishmania,non coding rna,post transcriptional control,translational regulation