Stanford Mineral-X is offering postdoctoral fellow positions within the Department of Earth & Planetary Sciences at Stanford University. Postdoctoral researchers will be developing data scientific and machine learning approaches for accelerating (critical) mineral exploration and discovery. One goal is to redefine the traditional knowledge-based geological interpretation process, particularly at the regional scale, by harnessing state-of-the-art machine learning and AI techniques. The machine-generated interpretations will rigorously adhere to geological principles, just as the outcomes typically obtained through expert knowledge-based approaches. The research will use extensive geophysical, geochemical, and geological data from real-world field cases. The postdoc will collaborate closely with both academic and industrial research partners at Mineral-X.
- Ph.D. in geosciences, geological engineering, geostatistics, geophysics, geochemistry, mining engineering, Earth and environmental sciences, computer science, or related subjects.
- Research excellence in related areas as demonstrated through publications.
- Quality of research papers (1-2 sample papers) – either published or working papers.
- Experience with real, large datasets, and data wrangling.
- Cover letter explaining your interest in becoming a postdoc with the respective research at Mineral-X (500 words max).
- Curriculum Vitae (CV)
- Description of your dissertation research and broader research agenda (1 page)
- One representative writing sample (published or unpublished)
- List of three reference contacts