GFZ is Germany's national centre for solid Earth research. We advance the understanding of dynamic processes to address global challenges, from mitigating the impacts of natural hazards and sustaining our habitat amid global change to responsibly managing georesources. We are part of the Helmholtz Association, the largest German scientific organisation. With around 1,200 employees as well as ca. 500 guest researchers, we contribute to the Helmholtz Research Field Earth and Environment, aligning cutting-edge research with societal relevance and international collaboration. Our work integrates multidisciplinary studies across Earth's system components, leveraging advanced technologies and infrastructure to research solutions and to transfer our knowledge to society. We are doing this according to our vision: “Taking the pulse of our Earth to safeguard a habitable planet”.

The Priority Program DEFORM of the German Research Foundation is funding multi-disciplinary research into the Adriatic Plate and its plate boundaries. The project represents the German contribution to the international AdriaArray initiative, a seismic array encompassing ~1500 seismic stations with 64 contributing institutions. Within this project, we are also operating a high-density seismic array (“Large-N array”) in western Greece and southern Albania encompassing nearly 800 sites, straddling the boundary between continental and oceanic subduction. This region carries the signature of a vibrant geodynamic history and shows different deformation styles in close vicinity.

The section for seismology at GFZ offers two PhD projects within this programme: 

Project 1: Seismological imaging of attenuation and scattering in the circum-Adriatic region

We investigate the attenuation and scattering properties of the crust in the wider Adriatic region.  You will employ scattering theory to separate the effects of wave scattering and anelastic attenuation on seismic wave propagation. You will use state-of-the-art inversion techniques to image the spatial distribution of subsurface heterogeneity to illuminate the imprint of past and present deformation.

Project 2: Generation and analysis of a high-quality seismic catalogue in Greece and Albania with Deep Learning

We leverage the data from the Large-N seismic array as well as an offshore fibre-optic cable, which is being interrogated with Distributed Acoustic Sensing (DAS), to derive a catalogue of the seismicity in the area at unprecedented resolution. Leveraging and improving state-of-the-art machine learning techniques, template matching and other techniques, you will derive a high precision catalogue of seismic activity down to very small magnitudes and analyse statistical patterns in order to understand how large-scale deformation is resolved onto faults in a region of diffuse deformation.

Your responsibilities:

Both projects:

• Study of relevant scientific literature
• Analysis of seismological data from earthquakes and/or ambient seismic noise
• Interpretation of your results in terms of geodynamic implications
• Present at international conferences and interdisciplinary workshops within the SPP DEFORM and the AdriaArray project
• Publish in peer-reviewed scientific journals
• Participate in seismological fieldwork (optional)

Project 1:

• Adapt and implement numerical simulation codes for seismic energy propagation in heterogeneous media using radiative transfer theory
• Generate regional models of attenuation and heterogeneity using advanced seismic imaging
• Interact with project partners to integrate observations into the known deformation history

Project 2: 

• Adapt and apply machine learning techniques for the detection and location of earthquakes of different sizes in Greece
• Interact with geologists and geodesists to understand the deformation budget and how it interacts with structural controls
• Improve the methodological approaches to the requirements of the data set

Your qualifications:

• (at start of employment): MSc in geophysics, physics or computer science/mathematics or related disciplines
• Experience in the analysis of seismological data
• Programming in Python
• Project 2: (preferred) Knowledge of machine learning, or experience in processing large datasets or experience with the analysis of local seismicity
• Fluency in English, both oral and written