2026 Phd Residency, Earth Scientist Ai Resident, Early Stage Project
X9
Mountain View, CA, United States
Base: $109,000 - $157,000; bonus/equity: not speci...
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Apply advanced ml and geophysics computing
Research at interface of geology/geophysics/seismology and ml
Strong programming skills in python
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X is seeking PhD candidates for its Earth Scientist AI Residency, focusing on innovative projects at the intersection of geophysics and machine learning. The position requires strong programming skills and research experience in relevant fields, offering a unique opportunity to work on impactful projects while gaining exposure to AI technologies.
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Job Summary
Collaborate with confidential X Project team to apply advanced ML and geophysics computing techniques to their project's mission.
This project aims to push the limits of science and modeling as we know them and to prove how ML can radically accelerate our understanding of the world.
Throughout your AI Residency you can expect to be embedded into one of our confidential or public X projects and get paid competitively and receive benefits.
Matching Summary
Match Score: 75
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X is seeking PhD candidates for its Earth Scientist AI Residency, focusing on innovative projects at the intersection of geophysics and machine learning. The position requires strong programming skills and research experience in relevant fields, offering a unique opportunity to work on impactful projects while gaining exposure to AI technologies.
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Salary
Base: $109,000 - $157,000; Bonus/Equity: Not specified; Benefits: Google benefits
Skills & Requirements
Must-have
Apply advanced ML and geophysics computing
Research at interface of geology/geophysics/seismology and ML
Strong programming skills in Python
Proficient with ML frameworks
Nice-to-have
Moonshot thinking and tech talks
Engage with AI/ML community
Research in full waveform inversion
Publications in relevant conferences
Key Requirements
PhD program in Geology, Geophysics, Seismology, ML, Physics, or Statistics
Completed coursework in geophysics, linear algebra, signal processing, ML