Thread: Post-doctoral Researcher – Machine Learning and Earthquake Slip Processes

Started: 2017-01-17 17:54:34
Last activity: 2017-01-17 17:54:34
Forwarded on behalf of:
Andrew Delorey
Los Alamos National Laboratory

Job Title: Post-doctoral Researcher – Machine Learning and Earthquake Slip Processes

Location: Los Alamos National Laboratory, NM

Summary: The mission of the Earth and Environmental Sciences (EES) Division of Los Alamos National Laboratory is to solve complex problems of importance in environment, energy, and national security by using our capabilities in earth and environmental sciences. The division is a highly interactive, well-funded research organization with an annual budget of approximately $100 million and a staff of approximately 240. The core disciplines of EES Division include Geology, Geochemistry, Geophysics, Geodynamics, Geography, Hydrology, Atmospheric Science, Ecology, Environmental Science, Computational Science and Geotechnical Engineering. The disciplines are organized into groups within the division, which consist of 30-40 Scientists, with approximately 20 support staff, post-docs, and students.

This job posting is for 1 (one) postdoctoral position in the Geophysics Group (EES-17). EES-17 performs research and development nonlinear acoustics, seismology, fault physics geology and geodynamics.

In this area of research we conduct experimental, theoretical and simulations of earthquake fault processes. We analyze these data applying classical signal processing and machine learning techniques with the purpose of inferring the physics of faulting and to determine if we can place time constraints on the failure time.

EES-17 is looking for a creative postdoc to join our interdisciplinary team. The successful candidate will take a role in analyzing experimental, simulation and seismic data applying classical signal processing techniques and especially machine learning and will be expected to conduct research independently, publish results in peer-reviewed journals and present at conferences.

Minimum Job Requirements: Candidates with a strong background/experience in all of the following areas are invited to apply:

Experience in Machine Learning
Experience in Geophysics and/or Materials Science (a geoscience background is preferred)
Strong understanding of Mechanical behavior of materials under geologic loading conditions
Proficiency in Python, Fortran, C, and C++
Excellent written and communication skills in English
Significant code development experience and an understanding of computational methods
Motivation to achieve in an independent work environment and also the communication skills to interact with a multidisciplinary, integrated team

Additional Desired Expertise:

Code development experience
Laboratory experience
Big data handling experience
Experience with numerical modeling (e.g. finite element, finite difference, discrete elements) for simulating fault processes, or experimental background in fault physics is desired.
Solid understanding of materials science and or earthquake physics
Excellent publication record in the field of materials science or geophysics

Education: A Ph.D. in Machine Learning, Geophysics, Materials Science, Mechanical Engineering, Solid Mechanics or related fields is required. The candidate must have completed all Ph.D. requirements by commencement of the appointment and be within 5 years of completion of the Ph.D.

Notes to Applicants: Regular post-doctoral appointments are for two years and are renewable for a third year. Outstanding candidates (with approximately 15 – 20 articles in reputable, peer-reviewed journals) may be eligible for a LANL Director's Fellowship.

Equal Opportunity: Los Alamos National Laboratory is an equal opportunity employer and supports and diverse and inclusive workforce.

Where you will work: Located in northern New Mexico, Los Alamos National Laboratory (LANL) is a multidisciplinary research institution.

To apply for this position, go through LANL’s online application system at

position IRC53703. See
Please also send a copy of your resume to Dr. Paul Johnson paj<at>
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