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Postdoctoral Scholar

The Pennsylvania State University
remote work
United States, Pennsylvania, University Park
201 Old Main (Show on map)
May 21, 2026
APPLICATION INSTRUCTIONS:
  • CURRENT PENN STATE EMPLOYEE (faculty, staff, technical service, or student), please login to Workday to complete the internal application process. Please do not apply here, apply internally through Workday.
  • CURRENT PENN STATE STUDENT (not employed previously at the university) and seeking employment with Penn State, please login to Workday to complete the student application process. Please do not apply here, apply internally through Workday.
  • If you are NOT a current employee or student, please click "Apply" and complete the application process for external applicants.

Approval of remote and hybrid work is not guaranteed regardless of work location.For additional information on remote work at Penn State, seeNotice to Out of State Applicants.

This is a term position; length of the term will be discussed during the interview process. Continuation past the termlengthdiscussed willbebasedonuniversityneed,performance,and/oravailabilityoffunding.

POSITION SPECIFICS

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

Applicants must 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 is required.

Candidates should possess excellent written and verbal communication skills, be able to work independently and have excellent computer skills. Clear demonstration of computer coding skills and use of data analysis software is desirable.

Interested candidates should submit the following:

  • An application letter highlighting qualifications for the position

  • A curriculum vitae including educational background, employment history, and a list of peer reviewed publications

  • Research statement of your interests in the context of desired qualifications

  • Contact information for three references.

BACKGROUND CHECKS/CLEARANCES

Employment with the University will require successful completion of background check(s) in accordance with University policies.

BENEFITS

Penn State provides a competitive benefits package for full-time employees designed to support both personal and professional well-being.

For more detailed information, please visit ourBenefits Page. (Note: For Postdoctoral benefits, please see our Postdoctoral Benefits page.)

CAMPUS SECURITY CRIME STATISTICS

Pursuant to the Jeanne Clery Disclosure of Campus Security Policy and Campus Crime Statistics Act and the Pennsylvania Act of 1988, Penn State publishes a combined Annual Security and Annual Fire Safety Report (ASR). The ASR includes crime statistics and institutional policies concerning campus security, such as those concerning alcohol and drug use, crime prevention, the reporting of crimes, sexual assault, and other matters. The ASR is available for review here.

EEO IS THE LAW

Penn State is an equal opportunity employer and is committed to providing employment opportunities to all qualified applicants without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability or protected veteran status. If you are unable to use our online application process due to an impairment or disability, please contact 814-865-1473.

Penn State is committed to and accountable for advancing equity, respect, and belonging. We embrace individual uniqueness, as well as a culture of belonging that supports equity initiatives, leverages the educational and institutional benefits of inclusion in society, and provides opportunities for engagement intended to help all members of the community thrive. We value belonging as a core strength and an essential element of the university's teaching, research, and service mission.

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