Assessing the risk of complex systems to natural hazards induced by climate and its change is an important and challenging problem. In today’s intricate socio-technological world, characterized by strong urbanization and technological trends, the connections and interdependencies between exposed elements are crucial. In this context of complex relationships, this PhD research aims to explore the potentiality of using graph theory in risk assessment of catastrophic hazards. It will progress on the activities at IUSS on the development of an innovative holistic approach (doi:10.5194/nhess-20-521- 2020) that allows to analyze risk in complex systems based on a graph, the mathematical structure to model connections between elements. The approach suggests representing the system's exposed elements and their connections using a weighted and redundant graph (doi.org/10.3390/w13202830). This method evaluates network properties to emphasize the centrality of certain "critical" exposed elements.The focus of the research will be to analyze how the percolation threshold and network fragmentation could be used to explains a system's resilience after disruption of extreme natural hazards (e.g., flood), distinguishing between the connected and fragmented phases and determining whether the system can maintain its structure or completely fail. Furthermore, the graph will be used to propagate impact into the system, for not only direct but also indirect and cascading effects.

The ideal candidate will have experience with most of these topics: network analysis, quantitative risk assessment, statistical analysis and large dataset. The candidate should be passionate on research topics, hardworking, self-motivated, have an open-mindedness to look for new ideas of doing things and creativity in analytical thinking to extract meaning from sets of data. The candidate should be able to collaborate with the rest of the research team and effectively communicate to colleagues with different backgrounds. Competence on programming languages is required, as well as familiarity with tools and package for network and spatial analysis (e.g., iGraph, Gdal).

IUSS mission is to provide advanced education to undergraduate, graduate students, fundamental and applied research. At IUSS, PhD candidates will find a multidisciplinary environment offering opportunities for developing academic and professional tools. The candidate will join the research centre on Climate change impAct studies for RISk MAnagement (CARISMA). The team is composed by STEM and Social scientists working in the prism of CC on data analysis/modelling of Earth and economic system processes; impact/risk assessment of extreme events. The ideal candidate will have experience with most of these topics: graph theory, statistical analysis, quantitative risk assessment and large dataset.