Computational Geologist

Responsibilities

• Develop, validate, and refine 3D geological and structural models from integrated datasets including drillhole logs, geochemical assays, geophysical surveys, and remote sensing imagery.
• Design and execute geophysical inversion workflows using tools such as SimPEG, Res2DInv, or equivalent, and assess the geological plausibility of recovered physical property models.
• Interpret gravity, magnetic, electromagnetic, and resistivity datasets in the context of regional geological frameworks and known mineralization styles.
• Build and maintain geological knowledge bases for target commodity systems (porphyry copper, orogenic gold, sediment-hosted copper, heavy mineral sands), encoding deposit-level geological rules into computational workflows.
• Collaborate with the machine learning team to ensure geological constraints, conceptual deposit models, and physical laws are properly embedded into neural network architectures and training pipelines.
• Contribute to mineral prospectivity mapping by preparing, quality-controlling, and fusing multi-source geodatasets for predictive modeling.
• Support the development of Deep Optica's synthetic geology engine by defining realistic geological scenarios, alteration assemblages, structural geometries, and weathering profiles for simulation.
• Prepare technical deliverables for clients including geological interpretations, target generation reports, and methodology documentation across diverse geological terrains.

• MSc or PhD in mining-related geology, geophysics, economic geology, or a closely related geoscience discipline.
• Strong foundational knowledge of igneous, sedimentary, and metamorphic petrology, structural geology, and ore deposit geology.
• Demonstrated experience with geophysical data processing and interpretation, particularly potential field and electromagnetic methods.
• Proficiency in at least one geological modeling or geophysical inversion software package (Leapfrog, Gocad/SKUA, Oasis Montaj, SimPEG, or Model Vision).
• Working proficiency in Python for data manipulation, visualization, and scripting of geoscientific workflows.
• Familiarity with geostatistical methods including variography, kriging, and spatial estimation.
• Understanding of how geological and geophysical constraints can be formulated for machine learning applications is a strong advantage.

• Experience working on mineral exploration projects in Africa, the Middle East, or South America.
• Familiarity with remote sensing data for geological mapping, including multispectral and hyperspectral imagery.
• Exposure to physics-informed machine learning or geoscience simulation frameworks.
• Prior work with airborne geophysical surveys such as gravity gradiometry, magnetics, or AEM.
• Knowledge of environmental geoscience applications including soil contamination assessment and land degradation monitoring.
• Bilingual in English and Mandarin is a plus given our cross-regional operations.

The opportunity to work at the frontier of AI and earth sciences, shaping how the mining industry discovers and evaluates mineral resources. A lean, technically ambitious team where your geological thinking directly influences product development and client outcomes. Exposure to diverse global projects and the chance to see your models tested against real subsurface data across multiple continents.