Postdoc position in Machine learning applied to Geochemistry at ETH Zürich

The Experimental Petrology Group at the Department of Earth and Planetary Sciences invites applications for a postdoc position dedicated to applying machine learning to large geochemical datasets with a focus on alkaline magmatism including carbonatites. Candidates should have experience with machine learning (or more general modern numerical techniques) and a keen interest in applying quantitative methods to characterise magmatic processes geochemically.

This postdoc will be part of a project that addresses the realm of alkaline and carbonatite magmatism and their mineralizations, including both magmatic and fluid-mediated processes. The idea of this position is on one hand to apply modern mathematical tools to existing geochemical data or databases in order to better understand petrological processes ranging from mantle melting to lithospheric interaction to final crystallization, and on the other hand to help identifying key processes or correlations that merit experimental verification. The successful candidates will be part of a group of about twelve PhDs and postdocs focused on the petrology and geochemistry of alkaline systems; one part of the group working on natural alkaline complexes, the other part on experiments dedicated to the alkaline series (s.l.).

The position is available immediately and should be filled in 2027. The annual postdoc salary starts at ~90'000 CHF. Initial appointment will be for 2 years, potentially renewable to up to 5 years. The successful candidate is expected to fulfil some teaching duties. Inquiries and applications in the form of a single pdf-file (including a statement of research interests) should be addressed to Max W. Schmidt ( E-Mail auf earthworks-jobs.com ansehen ).