data science

Spatio-temporal copper prospectivity in the American Cordillera predicted by positive-unlabeled machine learning

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Porphyry copper deposits contain the majority of the world’s discovered mineable reserves of copper. While these deposits are known to form in magmatic arcs along subduction zones, the precise contributions of different factors in the subducting and overriding plates to this process are not well constrained, making predictive prospectivity mapping difficult. Empirical machine learning-based approaches … Read more…

Applied Geochemistry: Multivariate statistical analysis and bespoke deviation network modeling for geochemical anomaly detection of rare earth elements

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Rare earth elements (REEs), a significant subset of critical minerals, play an indispensable role in modern society and are regarded as “industrial vitamins,” making them crucial for global sustainability. Geochemical survey data proves highly effective in delineating metallic mineral prospects. Separating geochemical anomalies associated with specific types of mineralization from the background reflecting geological processes … Read more…

PhD scholarship in Deep-Sea Sediments and Paleoclimate

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This PhD project with Dr. Adriana Dutkiewicz in the Univ. of Sydney EarthByte Group is aimed at reconstructing the evolution of the deep-sea carbon reservoir and its impact on the long-term global carbon cycle as part of an ARC-funded Future Fellowship. It includes a stipend allowance of $28,854 per annum for three years (with an … Read more…