This Ph.D. Course aims at the advanced training of students in the field of the Earth System Science, through a multidisciplinary approach, where specific skills integrate with modeling and computational tools that allow to effectively tackle complex problems. Special attention is devoted to the interactions between Mathematics, Scientific Computing, Data Science, Fluid Dynamics, and Earth Sciences.
This course promotes the preparation of students through the investigation of the scientific themes developed by the research groups belonging to the departments and the research institutions directly involved in the program, as well as through international collaborations with qualified foreign structures that provide students with the opportunity to attend training programs abroad.
In the field of Earth Science, advanced methods of investigation are developed in geological, geophysical, atmospheric, oceanographic, and climatological fields, with applications to the study of composition, structure, stratigraphy, evolution, and dynamics of our planet, from the close surface up to the deep structures and the characteristics at a global scale. Special attention is paid to issues related to the reduction of natural risks, finding of georesources, climate changes.
In the context of fluid mechanics, the study of the motion of the fluids is mainly addressed with reference to their transport properties, dispersion and mixing in environmental, industrial, biological processes, as well as to their interaction with the solid elements.
The laws, which these disciplines are based on, are generally expressed by highly complex mathematical models. The qualitative and quantitative study of such models requires the development and the application of sophisticated mathematical tools, and it represents a relevant and topical research field even from the mathematical point of view. Mathematical and computational modeling also requires an integrated use of different tools: methodologies for management and analysis of large amounts of information; tools for description, identification, multi-scale simulation of complex systems; methods for optimizing diagnosis and processes. In conclusion, Mathematics, Scientific Computing, and Data Science pervade the entire program, playing a central and unifying role.
Lines of research
Environmental fluid mechanics, fluid mechanics in industrial and technological processes, and in biological systems
Solid and fluid earth geophysics and geology
Mathematical methods and modeling in fluid mechanics and in geophysics, differential equations, and inverse problems: qualitative, computational, and numerical aspects.
Development and use of Data Science techniques, both for the construction of statistical big-data black-box models and for the analysis of complex models by using machine learning methods