Mendenhall Program: Earthquake-related opportunities

Lakes in southcentral Alaska archive sedimentary evidence of historic earthquakes, including the 2018, M7.1 Anchorage and the 1964, M9.2 Great Alaska earthquakes. We seek candidates with skills that combine seismology and sedimentology to determine quantitative estimates of shaking intensity and duration based on the characteristics of lake sediments that record past earthquakes.

The USGS seeks to advance understanding of active tectonic deformation on the seafloor by integrating existing and emerging technologies and analysis tools, particularly those applicable to hazardous phenomena such as earthquakes, tsunamis, aseismic fault slip, and ground failures. Research that combines multiple datasets to ameliorate spatially limited observations offshore are encouraged.

This research opportunity leverages machine learning techniques to better characterize earthquakes and Earth’s subsurface structure, enabling a deeper understanding of earthquake processes and impacts. 

We seek candidates to conduct basic or applied research into human-induced seismicity. Approaches can encompass any number of fields including seismology, numerical modeling, geomechanics, geodesy, and earthquake forecasting. Research into any cause of induced seismicity is welcome, including oil and gas operations, geologic carbon sequestration, and geothermal energy exploration and production.

Active faults in northern California pose risk to people and critical infrastructure but are challenging to characterize due to urbanization, a complex distributed fault network, rugged topography, and thick vegetation cover. We seek a Research Geologist who will focus on better characterization of active faults in the greater San Andreas fault system of northern California.

We seek applicants to develop a machine-learning model that can be used for earthquake forecasting. This model should provide probabilistic forecasts of the future earthquake rate, earthquake locations, and sizes.

Due to the paucity of observations for large magnitude events, major improvements in our ability to forecast earthquakes will likely depend on the utilization of more physics-based approaches.  We therefore seek a candidate to pursue the development and/or analysis of multi-cycle, physics-based simulators, a capability that is currently underdeveloped at the USGS.

Geomagnetic field disturbance can interfere with seismic monitoring (e.g., Ringler et al. 2020). Magnetic storms can introduce unwanted noise in seismic data, degrading event-detection threshold and affecting detailed analyses of seismograms. Under this proposal, this interference will be analyzed, resulting in improved seismic monitoring and improving our understanding of geomagnetic disturbance.

We seek a Mendenhall Fellow to conduct research into earthquake sequence evolution and how it may vary, to forecast seismic hazard and communicate earthquake activity across many timescales.  Topics could include earthquake sequence physics and/or statistics, near-real-time characterization, temporal and spatial variations on seismic hazard forecasts, and implementing research into model updates.

This Research Opportunity focuses on developing novel algorithms to improve NEIC’s accuracy and confidence in its global automatic solutions and to move the NEIC towards rapid, high-quality, automatic earthquake publication. The aim is to publish significant earthquakes more rapidly, shortening the time between when the public feels an event and when the corresponding data is published to the web.

This Mendenhall opportunity seeks proposals for research related to the modeling of earthquake-induced soil liquefaction and landslides, with particular focus on the integration of such research into USGS earthquake hazard products for both near-real time assessment and long-term forecasting of earthquake ground failure impacts.