Postdoctoral Researcher – Passive Seismic Imaging

FMLA Status: Exempt
Location: Salt Lake City, UT (hybrid)
Benefits Eligible: yes
Manager: Seismic Team Lead

Geothermal energy is the most abundant renewable energy source in the world. However, historically it’s been hard to find and expensive to develop. At Zanskar, we’re using advanced technology to find and develop new geothermal resources that make baseload geothermal a cost-effective and vital contributor to a carbon-free energy future. We are revolutionizing the exploration process, setting new industry standards for discovery rates by finding new prospects at an unprecedented scale and working to develop faster and cheaper with scale and reduced risk drilling. 

We're seeking a Postdoctoral Researcher in Passive Seismic Imaging to help advance how we image the subsurface using earthquakes and ambient noise. Working alongside our exploration and R&D teams, you'll help convert passive seismic signals into actionable items: images of basement depth, and fault geometry, that improve how we characterize prospects.

• Build velocity models and image basement depth, layering, and fault structure from passive arrays
• Locate and analyze microseismicity to map active faults, stress regimes, and structural controls
• Develop, benchmark, and refine passive seismic imaging methods
• Construct reproducible, well-documented processing pipelines (Python/ObsPy or equivalent) that scale to large datasets
• Work with the exploration and R&D teams to integrate passive imaging into prospect evaluation

Required

• Ph.D. (completed or near completion) in geophysics, seismology, or a closely related field
• Demonstrated research expertise in passive seismic methods such as ambient noise tomography or microseismic analysis, evidenced by peer-reviewed publications
• Strong foundation in seismic signal processing and inversion
• Proficiency in scientific computing and reproducible workflows (e.g., Python, HPC), with version control (e.g., Git/GitHub) a plus
• Ability to translate research-stage methods into practical, decision-grade tools under real-world data and time constraints
• Strong cross-disciplinary collaboration skills, able to communicate and integrate effectively with geologists, geophysicists, engineers, and data scientists