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Postdoctoral Research Associate - Computational Earth Sciences

Date: Jul 30, 2022

Location: Oak Ridge, TN, US, 37830

Company: Oak Ridge National Laboratory

Requisition Id 7806 


Oak Ridge National Laboratory is the largest US Department of Energy science and energy laboratory, conducting basic and applied research to deliver transformative solutions to compelling problems in energy and security.


We are seeking a Postdoctoral Research Associate who will support the Computational Earth Sciences group in the Computational Sciences and Engineering division (CSED), Computing and Computational Sciences Directorate (CCSD) at Oak Ridge National Laboratory (ORNL).  


The postdoctoral candidate will have experience in the fields of Computational Earth Sciences and Artificial Intelligence (AI) with a strong background in subsurface sciences and computational sciences. ORNL’s CESG conducts world-class research and development in Earth system modeling, large scale data analytics and machine learning (ML), and model-data integration at the US Department of Energy’s (DOE’s) Leadership Class Computing Facilities (LCFs).


Major Duties/Responsibilities: 

  • Use ML techniques to perform rapid analysis of real-time observations for forecasting pressure, saturation and stress evolution resulting from a carbon dioxide injection
  • Use ML techniques to build an effective, fast-to-evaluate surrogate model of the full-physics oil reservoir model
  • Use ML techniques to advance data-assimilation and history-matching in geological carbon storage modeling
  • Work with the AI research team to develop ML and data analytics algorithms, including dimension reduction, high-dimensional parameter optimization, and uncertainty quantification (UQ)
  • Develop computationally scalable ML algorithms and scale the algorithms on high performance computing (HPC) platforms
  • Collaborate with a diverse team of geoscientists, environmental scientists, and computational scientists within the CESG, the Environmental Sciences Division and across DOE Labs and partner universities to apply AI/ML algorithms and UQ methods aimed at accelerating real-time decisions in carbon storage applications
  • Publish research in peer-reviewed journals and present results at national and international conferences


Basic Qualifications:

  • A PhD in geosciences, engineering, hydrology, computational sciences or a related field, completed within the last 5 years


Preferred Qualifications:

  • Research experience in AI/ML and geoscientific modeling
  • Experience in HPC, particularly as applied to AI/ML algorithms and large-scale models
  • Knowledge of UQ and inverse modeling methods and AI/ML algorithms
  • Experience with data manipulation and analysis packages
  • Experience with the Linux operating system, LaTeX, Git, and Python
  • Familiar with Python programming using PyTorch and TensorFlow
  • Collaborative research capabilities as demonstrated by existing peer reviewed publications and technical proposals
  • Strongly motivated to perform and publish leading edge research
  • Excellent written and oral communication skills
  • Motivated self-starter with the ability to work independently and to participate creatively in collaborative teams across the laboratory 
  • Ability to function well in a fast-paced research environment, set priorities to accomplish multiple tasks within deadlines, and adapt to ever changing needs


Please submit three letters of reference when applying to this position. You can upload these directly to your application or have them sent to with the position title and number referenced in the subject line.


Instructions to upload documents to your candidate profile:

  • Login to your account via
  • View Profile
  • Under the My Documents section, select Add a Document


Applicants cannot have received their Ph.D. more than five years prior to the date of application and must complete all degree requirements before starting their appointment. The appointment length will be for up to 24 months with the potential for extension. Initial appointments and extensions are subject to performance and the availability of funding.


Moving can be overwhelming and expensive. UT-Battelle offers a generous relocation package to ease the transition process. Domestic and international relocation assistance is available for certain positions. If invited to interview, be sure to ask your Recruiter (Talent Acquisition Partner) for details.

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This position will remain open for a minimum of 5 days after which it will close when a qualified candidate is identified and/or hired.

We accept Word (.doc, .docx), Adobe (unsecured .pdf), Rich Text Format (.rtf), and HTML (.htm, .html) up to 5MB in size. Resumes from third party vendors will not be accepted; these resumes will be deleted and the candidates submitted will not be considered for employment.

If you have trouble applying for a position, please email

ORNL is an equal opportunity employer. All qualified applicants, including individuals with disabilities and protected veterans, are encouraged to apply.  UT-Battelle is an E-Verify employer.

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