Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Harnessing a New Generation of Solar Facilities and Machine Learning to Unveil the Quiet Sun's Hidden Magnetism (QUIET SUN)

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: Ireland
Call: MSCA Postdoctoral Fellowships 2024 (HORIZON-MSCA-2024-PF-01, 2024)
Start date: 2026-01-05
End date: 2028-01-04
Duration (months): 24.0
Total project cost (EUR): 252728.64
EU funding (EUR): 252728.64
Participants: 1
Project status: TERMINATED

This proposal will advance our understanding of solar magnetism to unravel the mystery of how the outer solar atmosphere is heated by leveraging a new generation of European observational facilities. The objectives are threefold: (1) Investigate the contribution of small-scale magnetic fields in the quiet Sun (QS) to chromospheric heating by tracking magnetic features across multiple atmospheric layers using high-resolution data from the SUNRISE III balloon-borne observatory. This facility offers unique advantages, such as providing high resolution observations in 14 spectral lines with three instruments while avoiding atmospheric distortions. (2) Reveal hidden magnetism in the QS using the Hanle effect, with observations from SUNRISE III's unprecedented suite of instruments, allowing simultaneous Zeeman and Hanle diagnostics for the first time ever. This will help determine the relationship between the magnetism below the Zeeman detection limit and the granulation pattern observed in the photosphere. I will apply novel machine learning techniques to maximize the physical insight achieved in objectives 1 and 2 from these observations. (3) Disentangle global and local dynamo contributions to QS magnetism by utilizing the first ever out-of-ecliptic observations of higher solar latitudes from the Solar Orbiter (SO) spacecraft. These observations will address key unresolved questions about the generation and evolution of small-scale magnetism and its contribution to solar activity. The proposal is underpinned by secured access to SUNRISE III data, with additional observations planned with SO and potentially the Daniel K Inouye Solar Telescope (DKIST), ensuring a comprehensive and risk-mitigated approach to achieving the objectives. The outcomes will provide significant new insights into the magnetic mechanisms driving solar atmospheric heating, with broader implications for stellar magnetism and space weather phenomena.

Keywords: quiet sun,solar atmosphere,machine learning,observations,spectropolarimetry
Pulmonary delivery of anticancer drug via an inhaled responsive nanogel with stealth ability and high targetability (PuDeRegels)

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: Chemistry
Countries involved: Greece
Call: Fostering balanced brain circulation – ERA Fellowships (HORIZON-WIDERA-2022-TALENTS-02, 2022)
Start date: 2024-02-15
End date: 2026-02-14
Duration (months): 24.0
Total project cost (EUR): 169326.72
EU funding (EUR): 169326.72
Participants: 1
Project status: SIGNED

In this project, I will investigate and develop nanogels incorporated into microgels containing encapsulated anticancer drugs. These nanogels will be delivered via the respiratory system to the lung, selectively swell and deliberate the therapeutic. Importance will be given to targeting moieties, stealth moieties, and biocompatibility. The delivery of drugs for lung cancer is limited but is under investigation and on the rise of inquiry. Some of the challenges this type of technology faces are the efficient encapsulation of the bioactive compound inside a nanocarrier, the targeted delivery, the release of the drug, the biocompatibility with the lung, and the avoidance of the macrophages. New methodologies for better delivery of therapeutics are of great importance at the National and International levels. New materials and technologies are emerging every year. The delivery of therapeutics for lung cancer is based mainly on intravenous therapies. Another way of introducing drugs into the area of importance in the lung could be pulmonary drug delivery as a good alternative. Pulmonary delivery is not a new technology but is strictly limited to specific conditions/illnesses. The research capitalizes on the existing strengths of the experienced researcher (ER) in polymer science and the expertise of the host institute in chemical biology in health, drug research, and biotechnology. It will lead to several publications in high-impact factor journals, transfer of knowledge and expertise that could be capitalized at an industrial level, thus contributing to the research output, distinctness, and economy of Europe. Overall, the fellowship will allow the ER to reintegrate into a long-term academic position after many years of fruitful research career in the academic sector in Spain. After this project, the ER will obtain new knowledge and training that will help him to establish a solid point for a better opportunity both in Academy and in Industry.

Keywords: polymers nanogels targetability stealth ability responsiveness biomaterials nanomaterials anticancer drug natural polymers
MarTe: Marine technology excellence hub for sustainable blue economy in Baltics (MarTe)

Framework: Horizon Europe — Widening Participation and Strengthening the European Research Area
Programme: Widening participation and spreading excellence
Theme: Improved access to Excellence
Destination: Improved access to Excellence
Action type: Coordination and support actions
Panel: Environment and Geosciences
Countries involved: Estonia,Latvia
Call: Excellence Hubs (HORIZON-WIDERA-2023-ACCESS-07, 2023)
Start date: 2025-01-01
End date: 2028-12-31
Duration (months): 48.0
Total project cost (EUR): 4999822.5
EU funding (EUR): 4999822.5
Participants: 13
Project status: SIGNED

The MarTe project aims to facilitate sustainable blue growth in the Baltic region by establishing Estonian and Latvian marine innovation Excellence Hub. This will be achieved through the collaboration of diverse stakeholders including academic institutions (TalTech, University of Tartu, Ventspils University of Applied Sciences, Latvian Institute of Aquatic Ecology), public sector (Environmental Investment Centre, Kurzeme Planning Region, Saaremaa Development Centre, Latvian Investment and Development Agency), industry (Association of Estonian Marine Industries, Port of Ventspils), and coastal communities (WWF, Baltijas Krasti, Saarte Koostöökogu). By leveraging quadruple-helix collaborations, MarTe will create a cross-border innovation strategy and supportive network for fostering new technologies throughout the marine industry value chain. Project objectives include collaborative R&D, ecosystem empowerment, and policy influence for advancing marine technologies, reinforcing stakeholder linkages, improving ecosystem capacity building, closing the knowledge gaps, supporting SMEs and startups, and elevating the visibility of the regional blue economy innovation ecosystems. In alignment with EU Green Deal and regional smart specialization strategies, the strategic framework focuses on marine technology innovation uptake in areas like offshore energy, smart vessels and ports, sustainable use of marine resources and marine ecosystem protection. Through a comprehensive approach encompassing stakeholder engagement and capacity building, MarTe strives for a significant impact on the sustainable blue economy in Baltics.

Keywords: blue economy,marine environment,baltic sea,marine technology,marine industry,innovation ecosystem,maritime technology
Setting the optimal balance between metabolite supplementation and deprivation in cancer therapy (METABALANCANCER)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Prevention,  Diagnosis and T reatment of Human Diseases
Panel description: Medical technologies  and tools for prevention, diagnosis and treatment of human diseases, therapeutic approaches and interventions , pharmacology, preventative  medicine, epidemiology and public health , digital medicine
Countries involved: Italy
Call: ERC STARTING GRANTS (ERC-2023-STG, 2023)
Start date: 2023-12-01
End date: 2028-11-30
Duration (months): 60.0
Total project cost (EUR): 1499250.0
EU funding (EUR): 1499250.0
Participants: 3
Project status: SIGNED

The goal of this proposal is to explore combinations of targeted metabolite supplementation and global nutrient restriction as a new strategy to reprogram tumor metabolism, to halt tumor progression and to improve response to treatments. Preclinical and clinical studies published by our group and by others showed that global nutrient restriction, in the form of cyclic fasting or fasting-mimicking diets (FMDs), produces desirable metabolic and immunologic effects that result in reduced tumor progression and in the prolongation of animal/patient survival. Of note, our unpublished results indicate that the supplementation of specific amino acids or fatty acids has in vitro and in vivo antitumor effects, which are strongly enhanced when metabolite supplementation is combined with nutrient starvation. By employing canonical cell biology and biochemical experiments, polysome/ribosome profiling, isotope tracing experiments and integrated omics (transcriptomic, proteomic, metabolomic) analyses in in vitro and in vivo murine and human tumor models, here we propose to: - identify the cell-autonomous and immune-mediated mechanisms at the basis of the antitumor effects of targeted metabolite supplementation in combination with global nutrient restriction; - identify the most effective metabolite supplementation-restriction strategy to be tested in a first-in-human clinical trial in patients with advanced triple-negative breast cancer. While the basic cancer research and medical oncology communities are engaged in a historical scientific and clinical diatribe on the use of nutrient deprivation vs. supplementation approaches to halt tumor progression and to improve patient survival, we will exploit our unprecedented ability to conduct parallel preclinical and clinical experimentation in the field of cancer metabolism to identify new and effective combinations of balanced metabolite supplementation and restriction, with relevant scientific and translational implications.

Keywords: in vitro models in vivo models anticancer immunity multi omics bioinfomatics
Artificial Intelligence-oriented supercomputing service environment (BSC AI Factory)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Digital, Industry and Space
Theme: Public-private partnerships
Destination: European High Performance Computing
Action type: Research and Innovation actions
Partnership: EUROHPC (JU-JTI)
Countries involved: Spain,Türkiye,Romania,Portugal
Call: Artificial Intelligence Factories (HORIZON-JU-EUROHPC-2025-AI-01-IBA, 2025)
Start date: 2025-04-01
End date: 2028-03-31
Duration (months): 36.0
Total project cost (EUR): 42000000.0
EU funding (EUR): 21000000.0
Participants: 6
Project status: SIGNED

This proposal represents the joint initiative of Barcelona Supercomputing Center – Centro Nacional de Supercomputación (BSC-CNS), Fundação para a Ciencia e a Tecnología, I.P. (FCT), the Scientific and Technological Research Council of Türkiye (Tubitak) and National Institute for Research & Development in Informatics (ICI Bucuresti), to develop and operate the BSC AI Factory, a new Artificial Intelligence Factory at the service of the European Union Artificial Intelligence innovation ecosystem. The BSC AI Factory project will deploy a comprehensive set of AI-oriented services, complemented with strong training, networking and hub facilities to boost the uptake and use of AI by industry with a special emphasis in SMEs and start-up companies, all of them based in the four participating countries and at the service of the European innovation community, designed specifically to meet Europe’s evolving AI needs, and running on a powerful upgrade of the EuroHPC JU MareNostrum5 supercomputer exploiting the most recent AI-oriented computing technologies.

Keywords: artificial intelligence,data lake,user support,smes,training,incubation,acceleration,innovation,ethics
Solar-Based Membrane Reactor For Syngas Production (SOMMER)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Climate, Energy and Mobility
Theme: Energy
Destination: Sustainable, secure and competitive energy supply
Action type: Research and Innovation actions
Countries involved: Germany,Spain,Greece
Call: Direct renewable energy integration into process energy demands of the chemical industry (HORIZON-CL5-2022-D3-02, 2022)
Start date: 2023-11-01
End date: 2027-10-31
Duration (months): 48.0
Total project cost (EUR): 4711516.25
EU funding (EUR): 4711516.25
Participants: 8
Project status: SIGNED

SOMMER will develop and demonstrate a novel carbon-neutral pathway for syngas production by integrating solar energy directly into a catalytic membrane reactor for the splitting of H2O and CO2 (e.g. captured from high carbon emitting industries or by direct air capture). This will allow SOMMER to overcome the fossil-based energy requirements for the production of syngas and to consume CO2 instead of natural gas as feedstock. Syngas, the mixture of H2 and CO, is a crucial intermediate product in the chemical industry. Thus, SOMMER will consider the entire value-chain from CO2 provision from a cement plant to syngas formation and further processing syngas to valuable and shippable products such as DME or methanol. The core of the SOMMER technology lies in the optimized energy integration of an emerging single-step CO2 and H2O thermochemical conversion process supported by highly selective catalysts and a dual-phase composite membrane, and a concentrated solar-thermal plant to supply the thermal energy demand. The main outcomes of SOMMER involve the experimental demonstration and evaluation of the innovative solar-powered membrane technology, and the development of high performance and cost-effective membranes as key components, thereby bringing the technology to the next level. SOMMER will advance membrane manufacturing via slip-casting, as a more mature approach, and via additive manufacturing to optimize the effective membrane surface area in the reactor. The concept is expected to have the future advantage of prolonged and flexible operation by switching between two operational Cases: I) Purely solar approach at 1500 °C and II) a biogas-supported approach at 900 °C. In addition, the identification of technological, ecological and economical potential for a flexible and highly efficient solar syngas production will contribute to the development of a detailed roadmap and provide the basis for the pre-commercialization through follow-up R&D development activities.

Keywords: catalytic membrane solar membrane reactor syngas production co2 conversion concentrated sunlight solar thermochemistry
Mapping the behavioural causes of weight change variability with genetic lottery (OBECAUSE)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: The Human Mind and Its Compl exity
Panel description: Cognitive science, psychology, linguistics
Countries involved: Estonia
Call: ERC STARTING GRANTS (ERC-2023-STG, 2023)
Start date: 2024-06-01
End date: 2029-05-31
Duration (months): 60.0
Total project cost (EUR): 1497500.0
EU funding (EUR): 1497500.0
Participants: 1
Project status: SIGNED

Obesity is a heritable chronic condition, costing 2% GDP worldwide. Many obesity treatments - behavioural, pharmacological, and surgical have been developed. Intriguingly, people’s responses to treatments vary widely - some may lose a lot of weight whereas others may even gain weight! To predict such weight change variability, close to 200 measures have been proposed in the past. The measures can be organised into a PEBBL framework across five domains – Psychosocial, Environment, Behavioural, Biology, and Life quality. Still, there are too many measures to be used as predictors or intervention targets. To move the field forward, we propose a novel 3-step OBECAUSE pipeline consisting of consolidation, genomic causation, and validation. 1) In consolidation, we will use machine learning to find best-predicting PEBBL measures in several large-scale weight loss datasets. The PEBBL measures will be integrated into a new PEBBL short questionnaire with wide coverage and good psychometric properties. The questionnaire will be then distributed to all participants of Estonian Biobank to study the genomics of PEBBL. 2) For genomic causation, we will detect genetic variants behind PEBBL measures and weight change. Knowing these variants enables discovering additions to the PEBBL framework through genetic correlations and functional mapping. Importantly, as genetic variants are randomised through genetic lottery, they enable systematic causal mapping of PEBBL measures that have causal effects on weight change. 3) For validation, these causal measures will be used as inputs to design an OBECAUSE toolbox of weight loss interventions. The value of these interventions will be tested in a commercial weight loss app. In summary, the OBECAUSE pipeline of narrowing scattered associations down to potential causal mechanisms with machine learning and genomic causal inference will set a new standard for the behavioural health sciences allowing for quicker discovery of intervention targets.

Keywords: weight change,obesity interventions,mendelian randomisation,behavioural science,machine learning
IamHealth: New scalable microcapsule technology for production, protection, and delivery of sensitive bio-actives (IamHealth)

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): 2499999.0
EU funding (EUR): 2499999.0
Participants: 1
Project status: SIGNED

There is an urgent need for new therapies to cure and prevent life-threatening yet common conditions such as cancer, diabetes, and viral infections. Novel biologics and cell therapies offer a major promise, but their world-wide clinical deployment is still hampered by the sensitive nature of bio-active compounds. Microencapsulation technologies have the potential to revolutionize our healthcare system by improving the production, protection, and delivery of sensitive bio-actives such as stem cells and vaccines. However, current microencapsulation methods are either too harsh, thereby causing damage to the bio-actives, or too slow, unable to produce clinically or commercially relevant batch sizes. At IamFluidics, a deep-tech university spin-off from The Netherlands, we have addressed this problem with our patented IN-AIR MICROFLUIDICS™ technology. Our process enables precise, biocompatible, and scalable microencapsulation of sensitive bio-actives. Furthermore, the technology produces uniform microcapsules at rates up to 1000x faster than conventional high-resolution methods, without relying on hazardous shear mixing, high temperatures, or toxic chemicals. We have developed a portfolio of proprietary formulations that are plastic-free, biodegradable, and optimised for our IN-AIR MICROFLUIDICS™ process, together uniquely enabling production, protection, and controlled delivery of even the most sensitive ingredients as, for example, demonstrated with living pluripotent stem cells and beating heart muscle microtissues. Through the IamHealth project, we will contribute to solving grand challenges like ‘upscaling 3D cell culture’, ‘ultra-cold-chain-free bio-active storage’, and ‘controlled long-acting injectable biologics’. Concretely, our multidisciplinary team of 20+ talented experts will realise the production pilot plant, products, quality system, and organisation necessary to position IamFluidics as the partner of choice for encapsulating bio-active compounds.

Keywords: microencapsulation,cell therapy,bio actives,probiotics,stem cells,biologics
Next generation mechanistic models of retinal interneurons (NextMechMod)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Neuroscience and Disorders of the Nervous System
Panel description: Nervous system development, homeostasis and ageing , nervous system  function and dysfunction , systems neuroscience  and modelling , biological basis of cognitive processes and of behaviour, neurological and mental disorders – In humans and all other organisms
Countries involved: Germany
Call: ERC STARTING GRANTS (ERC-2021-STG, 2021)
Start date: 2023-01-01
End date: 2027-12-31
Duration (months): 60.0
Total project cost (EUR): 1499860.0
EU funding (EUR): 1499860.0
Participants: 1
Project status: SIGNED

Ever since the work Hodgkin and Huxley, models of neurons have been essential for our understanding of neural computations. Such models have been developed at diverse levels of realism, from linear-nonlinear cascade or black-box models to detailed compartmental models. While these approaches are commonly viewed as incompatible, they have attractive strengths from an epistemic point of view. In this project, I propose to develop a new generation of hybrid mechanistic models that reconcile these levels of modelling: they will consist of a compartmental model for the neuron of interest with inputs approximated by black-box models. I will leverage the power of these hybrid models to tackle one of the most challenging questions in visual neuroscience: the staggering diversity of amacrine cells, a major class of inhibitory interneurons in the vertebrate retina. Despite their diversity, they are the least understood class of neurons in the retina, in stark contrast to the remaining circuitry. While in mouse more than 60 types of ACs have been identified by single cell transcriptomics, only a handful has been studied at depth. I will build on the latest advances in machine learning to develop a framework for efficiently inferring the parameters of a hybrid mechanistic model. To constrain the model parameters, we will acquire two-photon calcium and voltage imaging data during natural stimulation. Further, we will extend our framework to incorporate transcriptomic information about gene expression collected via patch-seq into the inference procedure, allowing us to map the amacrine cells to genetically defined types. Thus, in this project, I propose to develop a toolset to systematically uncover the role of retinal amacrine cells during natural visual computations, and link it to its mechanistic basis, providing a path forward to solving one of the key remaining mysteries of visual neuroscience.

Keywords: simulation based inference,amacrine cells,multimodal data,mechanistic models,patch seq,two photon imaging,single cell transcriptomics,interneuron