Postdoctoral Scholar

Penn State University • University Park, IL

21h • Onsite

About The Position

The College of EMS - Energy Institute at Penn State invites applications for an immediate position of Postdoctoral Scholar to conduct research on projects in collaboration with Dr. Sanjay Srinivasan, who directs the Penn State Initiative for Geostatistics and Geo-Modeling Applications (PSIGGMA). This initiative currently supports a group of 5 researchers working on topics such as the application of reinforcement learning for optimum reservoir development, the application of machine learning and multipoint geostatistics for characterization of fractures and novel algorithms for the integration of time-lapse seismic data into models for CO2 plume movement during sequestration. These projects are supported through grants from NSF, DOE and the John and Willie Leone Family Endowment. Applications are sought from researchers working in the areas of advanced data analytics and machine learning applied to solve subsurface reservoir characterization and modeling related challenges. Specifically, expertise looking at geochemical, geomechanical, and hydrologic data sets, high-performance modeling capabilities and the development of a suite of AI technologies, including surrogate models, physics-informed machine learning, and digital twins to enhance engineering evaluation and control of the subsurface during characterization, drilling, stimulation, and/or production will be preferred.

Requirements

• Hold an advanced degree, Ph.D. or equivalent in petroleum/subsurface engineering, geophysics, AI/ML, geostatistics or related field by hire date.
• Strong background and training in reservoir characterization techniques and/or subsurface process modeling especially using advanced data analytics and machine learning approaches.
• Excellent written and verbal communication skills.
• Ability to work independently.
• Excellent computer skills.
• Clear demonstration of computer coding skills and use of data analysis software is desirable.

Nice To Haves

• Expertise looking at geochemical, geomechanical, and hydrologic data sets.
• High-performance modeling capabilities.
• Development of a suite of AI technologies, including surrogate models, physics-informed machine learning, and digital twins to enhance engineering evaluation and control of the subsurface during characterization, drilling, stimulation, and/or production.

Responsibilities

• Conduct research on projects in collaboration with Dr. Sanjay Srinivasan.
• Apply reinforcement learning for optimum reservoir development.
• Apply machine learning and multipoint geostatistics for characterization of fractures.
• Develop novel algorithms for the integration of time-lapse seismic data into models for CO2 plume movement during sequestration.
• Apply advanced data analytics and machine learning to solve subsurface reservoir characterization and modeling challenges.
• Utilize expertise in geochemical, geomechanical, and hydrologic data sets.
• Develop a suite of AI technologies, including surrogate models, physics-informed machine learning, and digital twins.

Benefits

• Competitive benefits package for full-time employees designed to support both personal and professional well-being.
• Postdoctoral benefits.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree