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.
Job placement opportunities
The program of this course is designed to prepare students to pursue different careers in research, teaching and industrial use of high technologies in the fields of earth science, fluid mechanics, applied mathematics, and their interactions.
The students will be in contact with several local and international environments and gain an important experience in both theoretical and applied problems that originate in the disciplines mentioned above. In addition, the students will develop familiarity and competence in using the most advanced tools (both modeling and experimental) for the analysis of complex physical systems, which will be of great use for future activity in public or private research centers, or for any work in companies with high technological content.
The Doctoral School of Environmental and Industrial Fluid Mechanics and the Doctoral Course in Earth Science and Fluid Mechanics, which the present course is a natural continuation and expansion of, have systematically partnered during the last ten years with the departments of several research institutions and services, such as INOGS, ICTP, ISMAR-CNR, ENEA, ARPA-FVG, as well as with various industries in the area. The scholarships funded by such institutions, or factories, and their very presence, stem from their need to acquire highly specialized personnel in the topics addressed in this doctoral program. The students of this course will then have, as a natural outlet, post-doctoral grants, or employment, within the organizations themselves.
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
The scholarships are awarded for 3 years and their yearly amount is € 15.343,28 gross (approximatively € 1130 net per month).
Admission is based on a competitive examination.
The Call for Applications (Notice of Competition) is available on our website.
For more information on the Programme, please consult the doctorate page.