Earthquake and Disaster Science Master's and Doctoral Programs

About

Earthquake and disaster science has evolved from being a field that can be addressed solely through individual disciplines such as geology, geophysics, or civil engineering, into a holistic science and engineering field shaped by the interaction of natural hazards, the built environment, critical infrastructure, social systems, and digital technologies. Increasing population density, rapid urbanization, climate change, and the complexity of infrastructure necessitate addressing disasters not merely as "natural events," but as multi-dimensional and systemic risks. In this context, earthquake and disaster science encompasses a broad problem area ranging from the formation of risk and the spread of effects to response capacity, recovery, and resilience processes.

In recent years, major earthquakes, climate-related disasters, and multiple crisis scenarios have clearly demonstrated the importance of addressing early warning systems, risk modeling, damage estimation, decision support mechanisms, and post-disaster recovery processes on a scientific basis. Projects such as the Natural Hazards Engineering Research Infrastructure (NHERI) supported by the National Science Foundation (NSF) in the USA, large-scale shaking tables and disaster research centers in Japan, and disaster risk reduction projects conducted under the Horizon program in Europe, demonstrate the positioning of earthquake and disaster sciences as an interdisciplinary, data- and model-based independent research field.

The Earthquake and Disaster Science Master's and Doctoral Programs aim to integrate earth sciences, engineering, data science, systems analysis, and decision support approaches within a single academic framework, in line with this global trend. The programs are based on a contemporary research approach that considers disasters not only from the perspective of physical damage but also in conjunction with critical infrastructure, urban systems, human behavior, and governance mechanisms. Quantitative modeling, big data analysis, simulation, and scenario-based assessment methods are among the program's key distinguishing components.