Subsurface Geoscience Deep‑Learning Postdoc

Los Alamos National Laboratory; Los Alamos (NM); On-site; USD 65,000 - 90,000; Full time

Job summary

Los Alamos National Laboratory's Environmental Sciences (EES) Division has an opening for a postdoctoral research associate to develop multi-modal deep learning models for subsurface geoscience applications, including seismic and geodetic data. The successful candidate will test state-of-the-art ML models, collaborate with LANL scientists and external partners, and have a PhD in a relevant STEM field.

The appointment is for two years with potential extension based on performance and funding, and

Qualifications

• Research experience in deep learning model and applications in subsurface geoscience
• Publication record including subsurface geoscience and deep learning applications
• Proficiency in programming languages such as Python, C/C++
• Experience using supercomputing and HPC resources
• Communication skills as evidenced by oral presentations at conferences
• Experience working on interdisciplinary teams
• Ability to obtain Q level clearance, which usually requires U.S. citizenship

Responsibilities

• Develop multi-modal deep learning models for subsurface geoscience
• Test state-of-the-art ML models for seismic and geodetic data
• Collaborate with LANL scientists and external academic partners
• Contribute to research over a two-year term with potential extension

Skills

Deep learning research

Publication record

Python

C/C++

HPC experience

Communication skills

Interdisciplinary collaboration

U.S. citizenship for Q clearance

Education

PhD in geodesy/seismology/subsurface geoscience/related STEM field

Tools

Supercomputing resources

Job description

Los Alamos National Laboratory's Environmental Sciences (EES) Division has an opening for a postdoctoral research associate to develop multi-modal deep learning models for subsurface geoscience applications, including seismic and geodetic data. The successful candidate will test state-of-the-art ML models, collaborate with LANL scientists and external partners, and have a PhD in a relevant STEM field.

The appointment is for two years with potential extension based on performance and funding, and