Lead AI Research Engineer — Remote, Subsurface Reservoirs

University of North Dakota; Grand Forks (ND); Hybrid; USD 112,000 - 137,000; Full time

Job summary

The University of North Dakota's Energy & Environmental Research Center seeks a Principal Applied AI Research Engineer or Geoscientist to apply AI and analytics to subsurface energy challenges, including reservoir characterization, production forecasting, and CO2 or hydrogen storage. The role supports both remote and hybrid work arrangements. A bachelor’s in a related field and 5+ years of data science experience in oil and gas are required, with strong ML and programming skills.

Qualifications

• 5+ years of project experience in data science for oil and gas.
• Experience applying AI/ML to engineering/geoscience datasets.
• Programming with Python, R, SQL, MATLAB, or Jupyter.
• Criminal History Background Check required.
• Cover letter and resume required.

Responsibilities

• Evaluate geoscience and engineering data with advanced analytics and ML to inform oil & gas development and storage.
• Integrate ML into upstream workflows and geophysical interpretation.
• Develop, validate, and deploy data-driven reservoir models and forecasts.
• Apply ML, uncertainty quantification, and statistical modeling to large datasets.
• Translate ML results into defensible engineering interpretations and reports.
• Promote AI/data analytics within the EERC and collaborate across teams.
• Support proposals, budgets, and client-facing deliverables.

Skills

AI/ML experience

Python

R

SQL

Geoscience data analysis

Reservoir engineering

Leadership

Mentoring

Education

Bachelor’s degree in petroleum/geological engineering

Advanced degree (MS/PhD) in related field

Tools

TensorFlow

scikit-learn

MATLAB

Python notebooks (Jupyter)

Job description

The University of North Dakota's Energy & Environmental Research Center seeks a Principal Applied AI Research Engineer or Geoscientist to apply AI and analytics to subsurface energy challenges, including reservoir characterization, production forecasting, and CO2 or hydrogen storage. The role supports both remote and hybrid work arrangements. A bachelor’s in a related field and 5+ years of data science experience in oil and gas are required, with strong ML and programming skills.