Application Guide

How to Apply for Postdoctoral Scholar — AI Researcher for Critical Mineral Discovery

at KoBold Metals

🏢 About KoBold Metals

KoBold Metals is a pioneering AI-driven mineral exploration company that leverages machine learning and geophysical data to discover critical minerals essential for electrification and combating climate change. Their unique approach combines cutting-edge AI with real-world exploration, making them a leader in the transition to renewable energy. Working here means contributing directly to the global energy transition while pushing the boundaries of AI and geophysics.

About This Role

This Postdoctoral Scholar role focuses on developing and deploying advanced AI and geophysical methods—such as muon tomography, seismic imaging, and multi-physics inversion—to discover critical mineral deposits like copper, lithium, and rare earths. The impact is substantial: you'll create 3D subsurface models with quantified uncertainty, optimize drilling decisions, and accelerate the discovery of materials vital for electric vehicles and renewable energy infrastructure.

💡 A Day in the Life

A typical day might involve coding in Python to implement a new neural network architecture for joint inversion of muon and seismic data, then running simulations on a GPU cluster. You'd collaborate with geophysicists to interpret results and refine models, and attend a meeting to discuss drilling targets based on uncertainty quantification. You might also draft a paper or present findings to the team.

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🎯 Who KoBold Metals Is Looking For

  • A recent PhD in physics, geophysics, or machine learning with strong Python skills (PyTorch/JAX) and experience in HPC/GPU computing.
  • Proven ability to develop and apply deep generative models or physics-informed neural networks to real-world inverse problems.
  • Track record of publishing in top-tier venues and comfort working with industry-scale, noisy field data.
  • Familiarity with geophysical inversion (gravity, magnetics, EM, seismic) and decision-under-uncertainty frameworks.

📝 Tips for Applying to KoBold Metals

1

Tailor your CV to highlight experience with multi-physics inversion or joint inversion of geophysical data—mention specific methods (e.g., muon tomography, seismic full-waveform inversion).

2

In your cover letter, explicitly connect your PhD research to one of the listed techniques (e.g., deep generative models for subsurface modeling).

3

Showcase any work with decision-under-uncertainty or optimal experimental design, as sequential data acquisition is a key part of the role.

4

Include a link to a GitHub repository with reproducible research or open-source contributions relevant to geophysics or AI.

5

Mention any experience with real exploration data or industry collaborations—KoBold values practical application over pure theory.

✉️ What to Emphasize in Your Cover Letter

['Emphasize your passion for applying AI to solve climate change challenges through critical mineral discovery.', 'Highlight specific technical expertise in multi-physics inversion, deep generative models, or physics-informed neural networks.', 'Demonstrate your ability to work with real-world, noisy data and collaborate with field teams.', "Express interest in KoBold's mission and mention their unique use of muon tomography and joint inversion."]

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🔍 Research Before Applying

To stand out, make sure you've researched:

  • → Read KoBold's recent publications or press releases about their AI-driven discovery of copper deposits in Zambia.
  • → Explore their use of muon tomography—understand the physics and how it complements traditional geophysics.
  • → Study their approach to decision-under-uncertainty, possibly by reviewing talks or papers by their CEO or CTO.
  • → Look into their partnerships with mining companies and how they transition from exploration to production.

💬 Prepare for These Interview Topics

Based on this role, you may be asked about:

1 Describe a time you built a multi-physics inversion framework; how did you handle different data types and uncertainties?
2 How would you design a sequential data acquisition strategy to maximize information value for drilling decisions?
3 Explain your experience with physics-informed neural networks or deep generative models for 3D subsurface modeling.
4 How do you ensure reproducibility and scalability in your research workflows?
5 What is your understanding of muon tomography and how would you integrate it with seismic or EM data?
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⚠️ Common Mistakes to Avoid

  • Don't submit a generic application—this role is highly interdisciplinary; failing to connect your skills to both AI and geophysics will hurt your chances.
  • Avoid ignoring the 'decision-under-uncertainty' aspect; many applicants focus only on inversion, but KoBold values optimal data acquisition.
  • Do not underestimate the importance of reproducibility and code quality—mentioning version control, testing, or containerization is a plus.

📅 Application Timeline

This position is open until filled. However, we recommend applying as soon as possible as roles at mission-driven organizations tend to fill quickly.

Typical hiring timeline:

1

Application Review

1-2 weeks

2

Initial Screening

Phone call or written assessment

3

Interviews

1-2 rounds, usually virtual

✓

Offer

Congratulations!

Ready to Apply?

Good luck with your application to KoBold Metals!

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