Closing Date: November 1, 2022
This Research Opportunity will be filled depending on the availability of funds. All application materials must be submitted through USAJobs by 11:59 pm, US Eastern Standard Time, on the closing date.
Please communicate with individual Research Advisor(s) on the right to discuss project ideas and answer specific questions about the Research Opportunity.
How to Apply
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Seismic monitoring and cataloging are optimized for tectonic earthquakes, however many other natural and manmade processes of societal interest (which we will refer to as “exotic sources”) also generate seismic and acoustic signals that are commonly recorded, but often ignored, by seismic monitoring networks. For example, landslides and other mass movements like outburst floods, pyroclastic flows, and lahars, generate seismic and acoustic signals that contain information about the timing, size, and dynamics of the events. Similarly, blast signals contain information about the timing and size of explosions related to volcanic eruptions or mining and other human activities. However, we are not currently able to easily or automatically detect and differentiate these “exotic” signals as they come across our monitoring networks. Also lacking is the theoretical framework or algorithmic basis to locate and characterize the physical properties (e.g., volume, energy) of such sources in a way that is analogous to earthquake monitoring. This is true on all scales, from local volcano monitoring networks where rockfalls may need to be differentiated from fumarole or glacial activity to global seismic monitoring where large, rapid landslides or massive glacial calving events may generate signals that evade our earthquake detection algorithms and go undetected and uncharacterized. Acoustic data from infrasound sensors is becoming increasingly available but is not well integrated with current monitoring and cataloging schemes. Infrasound data have particular value in the monitoring of processes at the surface that interact with the atmosphere, such as in volcanic eruptions or the catastrophic failure of a large landslide.
Routine monitoring for large, rapid mass movements and other exotic events including automated detection, location, classification, and characterization, would be advantageous to the mission of three of the USGS Natural Hazards Mission area programs, all of which are represented by the research advisors for this opportunity. The Landslide Hazards Program (LHP) collects data on landslide occurrence and processes, including conducting fundamental research on landslide dynamics, and seeks to improve methods for landslide situational awareness and early warning. The LHP has a specific requirement to monitor landslides in Prince William Sound, AK, using seismic and infrasound arrays (Barry Arm, Alaska Landslide and Tsunami Monitoring). The Volcano Hazards Program monitors volcanoes for explosive eruptions and large mass movements, including real-time detection of lahars (e.g., Monitoring Lahars at Mount Rainier). These are major hazards at many volcanoes in the US, making the rapid detection and characterization of such events of utmost importance; however, mass movements and explosions are not currently systematically cataloged or characterized. Finally, the Earthquake Hazards Program is responsible for global seismic monitoring and is an authoritative source of information on earthquake characteristics, impact, hazard and risk and also sometimes provides information on non-earthquake sources of societal interest (e.g., M 4.2 Landslide - 108 km N of Uummannaq, Greenland). Seismic monitoring networks detect non-earthquake signals which they need to differentiate from earthquake sources. Tools to automatically detect, classify, and characterize exotic sources could allow monitoring networks to better provide timely and actionable information about these events.
We seek proposals that aim to close the gap between earthquake monitoring and exotic source monitoring, specifically focusing on 1) advances in automatic detection and classification of exotic seismoacoustic sources and 2) research providing the scientific basis and tools or algorithms needed to move toward basic characterization of exotic sources from their seismic and acoustic signals (e.g., location, mass, energy, speed). These are large problems that no single proposal can fully address so we encourage tractable proposals that recognize the main challenges and propose a project that will target one or two specific barriers or objectives. We encourage applicants to give particular focus to mass movements since high-quality, labeled datasets already exist (e.g., Collins et al., 2022; Data Services Products: ESEC (Exotic Seismic Events Catalog), the field has been rapidly expanding and there is a wealth of recent research to build on (e.g., Allstadt et al., 2018), and this topic is relevant to several existing USGS projects and the interests of the research advisors. However, the choice of focus must be done with the realization that other types of exotic sources must be accounted for in some way in signal classification schemes to avoid misclassification.
We encourage candidates to include data-driven, cutting-edge techniques from other geophysical and scientific fields such as artificial intelligence (i.e., machine learning, neural networks, deep learning) that can leverage USGS High-Performance Computing resources for research purposes, while keeping in mind the ultimate goal is having forward looking and portable methodologies that can be operationalized and used in real-time. Also consider that good characterizations of past events used in the proposed work may be needed if not already available, so remote sensing and/or field investigations could be considered for collecting key independent data for some of the natural events of interest.
As there are many different research directions and study sites that a proposal could focus on, we very strongly encourage interested applicants to reach out to the research advisors to work together to find a project scope that is tractable, within the interest and skillsets of the applicant, and that aligns with USGS needs.
Interested applicants are strongly encouraged to contact the Research Advisor(s) early in the application process to discuss project ideas.
References:
Allstadt, K.E., Matoza, R.S., Lockhart, A.B., Moran, S.C., Caplan-Auerbach, J., Haney, M.M., Thelen, W.A., and Malone, S.D., 2018, Seismic and acoustic signatures of surficial mass movements at volcanoes: Journal of Volcanology and Geothermal Research, v. 364, p. 76–106.
Collins, E.A., Allstadt, K.E., Groult, C., Hibert, C., Malet, J.-P., Toney, L.D., and Bessette-Kirton, E.K., 2022, Seismogenic Landslides and other Mass Movements: U.S. Geological Survey data release, https://doi.org/10.5066/P90VGCSK.
Hayes, G. P., Earle, P.S., Benz, H. M., Wald, D.J. and Yeck, W.L. “National Earthquake Information Center Strategic Plan, 2019–23.” Report. Circular. Reston VA, 2019. USGS Publications Warehouse. https://doi.org/10.3133/cir1457.
Proposed Duty Station(s): Golden, Colorado or Anchorage, Alaska
Areas of PhD: Geophysics, seismology, computer science or related fields (candidates holding a Ph.D. in other disciplines, but with extensive knowledge and skills relevant to the Research Opportunity may be considered).
Qualifications: Applicants must meet one of the following qualifications: Research Geophysicist, Research Geologist, Research Computer Scientist, or Research Mathematician.
(This type of research is performed by those who have backgrounds for the occupations stated above. However, other titles may be applicable depending on the applicant's background, education, and research proposal. The final classification of the position will be made by the Human Resources specialist.)
Human Resources Office Contact: Danial Anthon, 303-236-9197, danthon@usgs.gov