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BRIDGING IGNEOUS PETROLOGY AND MACHINE LEARNING FOR SCIENCE AND SOCIETY: Deriving New Skills in Volcanic Hazard Assessment and the Economy of Critical Raw Materials

Project description

AI training for volcanic risk and critical raw materials economy

Volcanoes pose extreme risks to society. Yet magmas are not solely destructive: they also provide critical raw materials of paramount economic and societal importance. With the support of the Marie Skłodowska-Curie Actions programme, the REALISE project will equip a new generation of doctoral candidates (DCs) with advanced skills in volcanic hazard assessment, risk mitigation and exploitation of critical raw materials. The project will explore machine learning techniques to study magmas, gather novel petrologic data through advanced analytical methods, and advance computational flow dynamics and atomistic simulations. It will also investigate the applications of generative AI in igneous petrology. Through comprehensive training and research, DCs will engage with case studies in high-risk volcanic areas and key sites for critical raw materials deposits.

Objective

REALISE equips a new generation of Doctoral Candidates (DC) with cutting-edge skills in volcanic hazard assessment and the exploitation of critical raw materials by combining advanced petrological studies with Machine Learning (ML) algorithms and workflows. To achieve this goal, REALISE brings together experts in Earth Sciences and Artificial Intelligence (AI) in an unprecedented attempt to develop training-to-research paths, i.e. Individual Research Projects (IRP), focusing on four key research objectives: 1) Systematically investigating the use of ML techniques to probe the lifecycle of magmas; 2) Fusing complementary information derived from cutting-edge analytical techniques to gather unprecedented petrologic data; 3) Bridging the gap between physics and ML in petrologic modelling to develop ground-breaking computational flow dynamics and atomistic simulations; 4) Exploring the potential of Generative AI, Hypothesis formulation, and Symbolic Regression in petrological studies. By combining the research activities with comprehensive training on transferable skills, DCs engage with key study cases in either volcanic areas posing significant volcanic risk [e.g. Campi Flegrei and Etna (Italy), Pico (Azores), Fogo (Cape Verde), Mt Pelée (Martinique)] or great potential in critical raw material exploitation [i.e. Beauvoir rare metal granite (Imerys kaolinite and Li deposit; France), mono-mineralic ore layers at Bushveld Igneous Complex (South Africa) and Lithium-Cesium-Tantalum pegmatites at Manono-Kitotolo (Dem. Rep. of Congo)]. Upon completion, REALISE will largely persist by establishing a network that fosters collaborations between academia and industry, enhancing disaster awareness, and contributing to the exploitation of critical raw materials. Overall, REALISE represents a significant step forward in both understanding magmatic systems and managing their associated risks and resources, with far-reaching implications for society and the scientific community.

Fields of science (EuroSciVoc)

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Keywords

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Programme(s)

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Topic(s)

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Funding Scheme

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HORIZON-TMA-MSCA-DN - HORIZON TMA MSCA Doctoral Networks

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Call for proposal

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(opens in new window) HORIZON-MSCA-2024-DN-01

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Coordinator

UNIVERSITA DEGLI STUDI DI PERUGIA
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 845 265,24
Address
PIAZZA DELL UNIVERSITA 1
06123 Perugia
Italy

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Region
Centro (IT) Umbria Perugia
Activity type
Higher or Secondary Education Establishments
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

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Participants (7)

Partners (11)

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