Assistant Research Professor – Distributed Acoustic Sensing and Machine Learning
About The Position
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
- Ph.D. in geophysics, seismology, applied mathematics, computer science, or a related field by the date of hire
Nice To Haves
- Experience in DAS
- Experience in seismic modeling
- Experience in moment-tensor inversion
- Experience in machine learning
- Experience in scientific programming
- Experience in high-performance computing
Responsibilities
- Conduct physics-based wavefield simulations
- Generate synthetic DAS datasets
- Develop deep-learning models for seismic event detection, location, and full moment-tensor estimation
- Validate these methods using field observations from earthquakes and controlled-source experiments
- Contribute to publications
- Contribute to project reports
- Student mentoring
- Collaborations with university and national-laboratory partners
Benefits
- Comprehensive medical coverage
- Dental coverage
- Vision coverage
- Robust retirement plans
- 75% tuition discount for employees
- 75% tuition discount for eligible spouses and children
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Entry Level
Education Level
Ph.D. or professional degree
