No summary provided for this position.

A fully funded PhD position is available at the University of Leeds, focusing on the integration of artificial intelligence, geophysics, and remote sensing for sustainable mineral exploration. The successful candidate will join an interdisciplinary team and work on developing innovative methodologies for mineral prospectivity mapping using machine learning, specifically attention-based convolutional neural networks. The project will utilize multi-source geophysical data, including gravity, magnetic, radiometric, and hyperspectral remote sensing, to identify promising mineral exploration targets. Real-world case studies in the UK will be used to develop robust and environmentally sustainable exploration strategies. The position is funded through the YES DTN (Yorkshire Environmental Sciences Doctoral Training Network) and covers tuition, stipend, and research costs for 3.5 years. Applicants should have a strong background in geology, geophysics, or earth sciences (minimum 2:1), good numerical skills, and an interest in machine learning. Both UK and international students are eligible. Applications open on 17 November 2025 and close on 7 January 2026. For more information and to apply, visit the provided link or contact the supervisors via email.