April 4, 2019
Earthquakes induced by human activities, in particular subsurface injection of wastewater from oil production, has increased rapidly since 2011 and is now fluctuating in response to mitigation efforts and imposed restrictions. It is not clear how the interaction between fluid flow, stress within the crust, and pre-existing faults control the evolution of earthquakes, but this is the topic of a new collaboration between cyberinfrastructure experts, scientists and engineers. The earthquakes have produced damage in nearby structures, so anticipating the degree of shaking and the response of structures is key to reducing risk to local populations. In this project the student will have the opportunity to work with a team implementing real-time analysis of earthquake data from accelerometers and GPS sensors as well artificial intelligence algorithms to solve problems related to this geohazard.
Criteria for selection:
Good quantitative background in physics and mathematics and / or computational science as evidenced by GRE scores and difficulty of courses attempted in transcripts.
Experience or motivation to learn to apply these skills to numerical modeling and signal processing for solving problems that impact society.
Good background in analysis of environmental systems.
Experience or motivation to learn to apply these skills to new problems.
Maturity in approaches to solving research problems, and high level of organization.
Although the normal application process has closed for Fall 2019, the additional NSF funding available has prompted this new opportunity for students.
Complete applications should be prepared as follows in a single pdf attachment named lastname_firstname_cyber_gradapp.pdf and mailed to email@example.com :
Statement of research interests, transcripts, GRE scores, and CV which includes contact information for three reference letters.
Learn new data analysis techniques as you explore the effects of human induced earthquakes related to energy production that impact the safety of structures. This topic is sponsored by a National Science Foundation Cyberinfrastructure for Sustained Scientific Innovation grant at Scripps Institution of Oceanography.