Postdoctoral Scholar
Core
Conduct research on subsurface reservoir characterization and modeling using advanced data analytics and machine learning for CO2 sequestration and reservoir development.
Role type
Postdoctoral Scholar (Research)
Builds
AI technologies, surrogate models, physics-informed machine learning, and digital twins for subsurface engineering evaluation.
Domain
Energy / Petroleum Engineering / Geostatistics / Machine Learning
Deliverable
research
Required skills
advanced data analytics, machine learning, reservoir characterization, subsurface process modeling, geochemical data analysis, geomechanical data analysis, hydrologic data analysis, high-performance modeling, coding, data analysis software
Preferred skills
reinforcement learning, multipoint geostatistics, time-lapse seismic data integration, CO2 plume movement modeling
Technologies
Python, TensorFlow, PyTorch, MATLAB, OpenFOAM, Eclipse, CMG, Petrel, Seismic processing software
Responsibilities
Develop AI technologies and digital twins for subsurface characterization; analyze geochemical, geomechanical, and hydrologic datasets; collaborate on NSF/DOE-funded research projects; publish peer-reviewed research.
Seniority
Postdoctoral (Early-career researcher)