Integrated application of traditional petrological approaches and artificial intelligence techniques to the study of magmatic systems: implications for volcanology and critical raw materials research
Posted on: 19/03/2026
Deadline: 04/04/2026
Scientific-Disciplinary Group
04/GEOS-01 - Mineralogy, Petrology, Geochemistry, Volcanology, Georesources And Applications
Description
The project Will integrate quantitative petrology and machine learning techniques to reconstruct the physical, thermodynamic, and chemical evolution of magmatic systems across crustal reservoirs, The aims are to constrain magma genesis and differentiation, determine storage conditions, and pathways in trans-crustal plumbing systems. By combining mineral, glass and melt/fluid inclusion data with thermodynamic models and data-driven inversion, the project Will identify processes that drive intrusion vs. eruption and factors modulating eruptive style. In parallelF it Will quantify how critical elements (e.g., Li, PG' REE) become enriched, segregated, and empiaced to form fertile ore deposits at different crustal levels. The expected outcomes are improved frameworks for volcanic hazard assessment and predictive models linking magmatic processes to the formation of critical raw materials
Job posting website
Number of positions
1
Funding body
Università degli Studi di Perugia
View the original posting on the MUR website: Go to MUR website