MSc in Large-scale Data-Driven Mineral Prospectivity Mapping at Carleton University (Earth Sciences, Data Science, Geoscience)

Carleton University is offering two MSc funding opportunities in Earth Sciences, focusing on large-scale data-driven mineral prospectivity mapping. These projects are in collaboration with Natural Resources Canada (NRCan) and aim to advance Canadian methodologies for mineral potential modeling. The research will involve geoscientific data analysis, machine learning, statistics, and geodata science, with the goal of developing reliable and objective prospectivity products for critical mineral exploration. The MSc projects are ideal for students with backgrounds in Earth Science, Data Science, Geostatistics, Computer Science, Geology, or related fields. No prior experience with AI or geoscience is required, and the projects can be tailored to the candidate's research interests and experience. The work environment includes collaboration with a dynamic geoscience team at the Geological Survey of Canada, supporting the Critical Mineral and Geoscience Data Program. Applicants must have a Bachelor of Science degree with a thesis in a relevant field and experience with spatial data, machine learning, statistics, mathematics, and effective communication in English. The scholarship provides approximately $25,500 in the first year and $27,500 in the second year, totaling $53,000, with an expectation of 10 to 15 hours of work per week under the Research Affiliate Program. The deadline to apply is March 27, 2026, with the program starting in September 2026. To apply, submit your résumé and a cover letter outlining your qualifications and interest in the position. Proof of education credentials is required. The selection process values equity, diversity, and inclusion, and encourages applications from underrepresented groups. For more information, visit the provided links or contact the supervisor.