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.

Your responsibilities:

• Developing and using data analysis workflows to extract discrete faults from 3D, time-dependent geodynamic models and geophysical data sets
• Conducting and interpreting thermo-mechanical models using the geodynamic research software ASPECT
• Comparison and interpretation of fault characteristics from models and geophysical data
• Interacting and collaborating with other members of the Geodynamic Modelling Section and the Geophysics Department
• Presentation of results at scientific meetings and in publications in peer-reviewed journals

Your qualifications:

• Master`s degree (or equivalent) and a PhD in Earth Sciences, Physics, or Engineering
• Experience and knowledge of the development and use of data analysis techniques in geosciences
• Knowledge of and experience with geodynamic modelling, preferentially the ASPECT research code
• Experience in Python programming and model visualization
• Proven ability to work in a collaborative and multi-disciplinary environment
• Creativity and critical thinking skills and the ability to publish, as demonstrated by a record of original and innovative publications
• Capacity for international teamwork, and excellent communication skills
• Proficiency in spoken and written English, German is an asset