Rifts and rifted continental margins host significant natural resources, such as groundwater and geothermal energy, but are also sites of strong, infrequent earthquakes posing considerable natural hazard. To understand the occurrence of geohazards and georesources, we need to quantify how strain localises and how fault networks evolve in crustal-scale extensional systems. This project follows an innovative, multidisciplinary approach by using data analysis techniques in order to interpret big data sets from numerical geodynamic models and geophysical surveys.
This project will be embedded in GFZ’s Section 2.5 “Geodynamic Modelling”. The post-doctoral researcher's role will be to develop and employ techniques involving computer vision, network and graph analysis to quantify fault dynamics in time-dependent 3D numerical forward models as well as 2D and 3D geophysical data sets. Results will be compared to manual interpretations of both data types and interpreted in terms of their geodynamic context in order to shed new light on the dynamics of normal fault networks in space and time.
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