Postdoctoral Scholar — AI Researcher for Critical Mineral Discovery

Fully funded 3-year postdoctoral fellowship at Stanford Mineral-X, advised by Prof. Jef Caers, in collaboration with KoBold Metals, developing and deploying new methods for critical mineral exploration and resource definition. The scholar will develop and apply AI, muon tomography, seismic imaging, and geophysical inversion methods to discover and characterize copper, nickel, lithium, cobalt, and rare earth deposits using real exploration data from active field programs. More information here: https://postdocs.stanford.edu/postdoc-admins/policy/funding-rates-and-guidelines.

• Multi-physics inversion: Develop stochastic and ensemble inversion frameworks that jointly assimilate muon flux, seismic (active-source, passive, DAS), magnetics, gravity, and EM data into 3D subsurface property models with calibrated uncertainty.
• Muon tomography: Forward modeling, sensor placement optimization, and inversion of cosmic-ray muon attenuation data from borehole and surface detectors to constrain ore body density at depth.
• Machine learning for geoscience: Apply deep generative models, geostatistical priors, and physics-informed neural networks to regional-to-deposit-scale targeting and resource estimation. Build pipelines that respect geological process constraints rather than purely data-driven correlations.
• Decision under uncertainty: Extend Mineral-X’s intelligent agent framework to sequential data acquisition decisions (drill hole placement, geophysical survey design) that maximize information value per dollar.

• PhD (fully completed, and within 4 years of graduation) in physics, applied physics, geophysics, computational earth sciences, machine learning, applied mathematics, or related field.
• Strong Python proficiency (NumPy, PyTorch or JAX, scientific stack); experience with HPC, GPU computing, and reproducible research workflows.
• Track record of publishing in peer-reviewed venues and willingness to engage directly with industry collaborators and field data.

• Demonstrated research output in at least two of: geophysical inversion, Bayesian/probabilistic methods, deep learning, particle physics detection, or seismic imaging.
• Experience with muon transport simulation (GEANT4, CORSIKA), distributed acoustic sensing, or full-waveform inversion.
• Familiarity with mineral systems, ore deposit geology, or exploration workflows.
• Prior work with diffusion models, normalizing flows, or generative models.

• Term: Three years, fully funded. Competitive Stanford postdoctoral salary plus medical, dental, vision, and conference travel support.
• Location: Stanford, CA. Periodic travel to industry partner sites and field programs.

Start: Preferably Aug 1, 2026

Salary: $80,000 - $90,000

https://postdocs.stanford.edu/postdoc-admins/policy/funding-rates-and-guidelines