Geophysicist, Seismic Inversion (Senior - Principal - Advisor) Landmark - 211399 (Houston, TX, US, 77032)

Responsibilities Develop elastic full-waveform inversion and acoustic or elastic seismic-inversion methods for shot-gather, post-stack, and pre-stack AVO/AVA applications. Design AI and deep-learning approaches that improve seismic imaging, inversion, seismic facies classification, and seismic-to-petrophysical property mapping. Integrate seismic volumes, well logs, core measurements, rock-physics relationships, and geologic interpretations to construct high-resolution 3D reservoir-property models. Develop Python-based research prototypes, algorithms, and reproducible technical workflows using appropriate scientific-computing and machine-learning frameworks. Quantify uncertainty in predicted rock properties and fluid saturations using statistical, probabilistic, ensemble, or AI-enabled inverse-problem methods. Distinguish and evaluate epistemic and aleatoric uncertainty, analyze model generalization, and identify limitations in training data and model assumptions. Validate seismic, reservoir, and machine-learning models using blind-well tests, held-out data, physical consistency checks, and comparison with known subsurface observations. Incorporate sequence-stratigraphic frameworks, seismic facies, geostatistical principles, and petrophysical constraints into reservoir-characterization workflows. Collaborate with multidisciplinary R&D and product teams to define technical problems, prioritize experiments, assess feasibility, and translate successful research into usable software capabilities. Document methods, assumptions, experiments, results, model limitations, and recommendations, and communicate complex findings to technical and product stakeholders. Monitor advances in geophysics, AI, deep learning, and scientific computing, and contribute to technical publications, presentations, invention disclosures, and patents where appropriate. Qualifications Required Undergraduate degree in Science, Engineering, or a similar technical discipline. Minimum of four years of related experience in applied research, technology development, product development, engineering, scientific analysis, or a comparable technical field. Demonstrated experience applying scientific or engineering principles to seismic imaging, seismic inversion, quantitative interpretation, reservoir characterization, or a closely related technical problem. Proficiency in Python and experience developing scientific-computing, data-analysis, machine-learning, or deep-learning workflows. Experience designing technical investigations, experiments, model evaluations, or validation studies and interpreting the resulting data. Ability to document technical work, manage defined R&D deliverables, and communicate complex concepts and recommendations to multidisciplinary technical stakeholders. Preferred Master’s degree or PhD in Geophysics, Rock Physics, Petroleum Engineering, Applied Mathematics, Computer Science, or a related technical discipline. Experience with full-waveform inversion, pre-stack AVO/AVA inversion, post-stack inversion, quantitative interpretation, rock physics, or seismic reservoir characterization. Experience with PyTorch, TensorFlow, scikit-learn, or comparable AI and scientific-computing technologies. Experience with uncertainty quantification, probabilistic inversion, geostatistics, sequence stratigraphy, seismic facies classification, or 3D static reservoir modeling. Energy