Assistant Research Professor – Distributed Acoustic Sensing and Machine Learning

Penn State University; University Park (TX); On-site; USD 95,000 - 130,000; Full time

Benefits offered by this job

75% tuition discount

Job summary

Penn State University in University Park, PA, seeks a Research Assistant Professor to advance machine-learning methods for seismic source characterization using distributed acoustic sensing. You will run physics-based simulations, generate synthetic DAS data, and develop deep-learning models for event detection, location, and moment-tensor estimation.

The role involves publishing results, mentoring students, and collaborating with university and national-lab partners, with a term-length to be

Qualifications

• Ph.D. in geophysics, seismology, applied mathematics, computer science, or a related field by date of hire.
• Experience in DAS, seismic modeling, moment-tensor inversion, machine learning, scientific programming, and high-performance computing is highly desirable.

Responsibilities

• Develop physics-based wavefield simulations and generate synthetic DAS datasets.
• Create deep-learning models for seismic event detection, location, and full moment-tensor estimation.
• Validate methods using field observations from earthquakes and controlled-source experiments.
• Contribute to publications, project reports, student mentoring, and collaborations with partners.

Skills

DAS

Seismic modeling

Moment-tensor inversion

Machine learning

Scientific programming

High-performance computing

Education

Ph.D. in geophysics, seismology, applied mathematics, computer science, or related field

Job description

Approval of remote and hybrid work is not guaranteed regardless of work location. For additional information on remote work at Penn State, see Notice to Out of State Applicants.

This is a term position; length of the term will be discussed during the interview process. Continuation past the term length discussed will be based on university need, performance, and/or availability of funding.

Position specifics

Research Assistant Professor – Distributed Acoustic Sensing and Machine Learning

The Department of Geosciences at Penn State seeks a Research Assistant Professor to support a project developing machine-learning methods for seismic source characterization using distributed acoustic sensing (DAS). The successful candidate will conduct physics-based wavefield simulations, generate synthetic DAS datasets, develop deep-learning models for seismic event detection, location, and full moment-tensor estimation, and validate these methods using field observations from earthquakes and controlled-source experiments. The position will also contribute to publications, project reports, student mentoring, and collaborations with university and national-laboratory partners.

Requirements

Candidates must hold a Ph.D. in geophysics, seismology, applied mathematics, computer science, or a related field by the date of hire. Experience in DAS, seismic modeling, moment-tensor inversion, machine learning, scientific programming, and high-performance computing is highly desirable.

BACKGROUND CHECKS/CLEARANCES

Employment with the University will require successful completion of background check(s) in accordance with University policies.

Benefits

Penn State provides a competitive benefits package for full-time employees designed to support both personal and professional wellbeing. In addition to comprehensive medical, dental, and vision coverage, employees enjoy robust retirement plans. One of the standout benefits is the generous 75% tuition discount, available to employees as well as eligible spouses and children.

For more detailed information, please visit our Benefits Page. (Note: For Postdoctoral benefits, please see our Postdoctoral Benefits page.)

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EEO is the law

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