Senior Computational Geophysicist

1h1 hour ago

Zanskar

Salt Lake City, US · Full-time · $150,000 – $220,000

About this role

Zanskar is transforming geothermal exploration by combining geophysics, geology, and AI-driven modeling to increase discovery rates and reduce development risk. Geothermal energy contains ~2,300× more energy than all fossil fuels combined, yet has been difficult to discover and develop. We need a Senior Computational Geophysicist with hands-on experience in electromagnetic and/or potential fields methods to turn real field data into defensible subsurface interpretations.

This role focuses on streamlining and automating inversion workflows that incorporate structural, lithological, and hydrothermal constraints, ensuring models reflect geological reality. Lead stochastic and traditional inversions on active geothermal sites to produce subsurface models that de-risk drilling decisions. Work extensively with electromagnetic and potential fields data including heliTEM, magnetotellurics, gravity, and magnetic data.

Quantify uncertainty and assess model robustness in decision-critical settings while integrating inversion results with geological models, structural interpretations, well data, and drilling outcomes. Collaborate closely with geologists and ML researchers in a hybrid environment in Salt Lake City. Communicate results clearly, including uncertainties, assumptions, and recommended next steps.

Develop and maintain Python-based tools and pipelines that automate inversion workflows for consistent, repeatable results across many sites. Contribute to patentable methods and tools that advance geothermal exploration. Operate under imperfect data, time pressure, and evolving site understanding to set new industry standards.

Requirements

Hands-on inversion experience on real-world geothermal or subsurface projects across multiple sites and datasets
Direct experience with EM and/or potential fields methods (heliTEM, MT, gravity, and/or magnetics) from raw field data through to full inversion workflows
Strong programming skills in Python, including building reproducible, maintainable scientific software
Experience implementing or modifying inversion algorithms, with stochastic, Bayesian, and regularization-based approaches
Solid physical intuition for geophysical observables and ability to reconcile inversion results with geological, structural, and operational constraints
Comfort operating under imperfect data, time pressure, and evolving site understanding
Proven ability to collaborate across disciplines and communicate clearly about data support, limitations, and uncertainty

Responsibilities

Lead and execute stochastic and traditional inversions on active geothermal sites, producing subsurface models that de-risk drilling and development decisions
Work extensively with electromagnetic and/or potential fields data, including heliTEM, magnetotellurics, gravity, and magnetic data
Quantify uncertainty and assess model robustness in decision-critical settings
Integrate inversion results with geological models, structural interpretations, well data, and drilling outcomes
Develop and maintain Python-based tools and pipelines that automate inversion workflows
Collaborate closely with geologists and ML researchers
Communicate results clearly, including uncertainties, assumptions, and recommended next steps
Contribute to patentable methods and tools that advance geothermal exploration