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U.S. Department of the Interior (DOI)

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USGS Data Science – Geothermal Energy Fellowship U.S. Department of the Interior (DOI) in United States

Degree Level

Master's

Field of study

Computer Science

Funding

Full-time fellowship with annual stipend range of $107,400.00–$134,280.00, varying by location, education, and experience. Appointment is initially for three months and may be renewed contingent on funds.

Deadline

Nov 17, 2026

Country flag

Country

United States

University

U.S. Department of the Interior (DOI)

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Keywords

Computer Science
Data Science
Environmental Science
Geography
Spatial Analysis
Earth Science
Python Programming
Quantitative Analysis
Data Visualization
Spatial Statistics
Geothermal Engineering
Statistics
Geostatistic
ML

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About this position

This fellowship places a student within the U.S. Geological Survey’s Conventional Geothermal Assessments Task, part of the Energy Resources Program and affiliated with the Geology, Minerals, Energy, and Geophysics Science Center. The work is based in a multidisciplinary USGS research environment connected to offices in multiple western U.S. locations, with the center headquartered at Moffett Field, California.

The project focuses on compiling and analyzing spatial datasets to support mapping and estimation of conventional geothermal energy resources across the western United States, including Alaska and Hawaii. The fellow will work under mentor guidance as part of an assessment team using modern data-driven approaches, including machine learning, to study geothermal potential and uncertainty.

  • Spatial dataset compilation, management, and analysis for energy-resource assessment
  • GIS and geospatial analysis of geologic, geophysical, volcanic, and related datasets
  • Application of machine-learning and geostatistical methods to resource prediction and mapping
  • Collaboration with USGS scientists across geology, geophysics, GIS, volcanology, machine learning, and geostatistics
  • Training in complementary analytical tools within a team-based research setting

The fellowship is designed to build practical and interdisciplinary research skills in Earth science data analysis while contributing to USGS geothermal resource assessment work.

Funding details

Full-time fellowship with annual stipend range of $107,400.00–$134,280.00, varying by location, education, and experience. Appointment is initially for three months and may be renewed contingent on funds.

What's required

Applicants should have received or be currently pursuing a master's or doctoral degree in geoscience, data science, computer science, statistics, geography, engineering, or a related field. A minimum of a master's degree is required, and a doctoral degree is preferred. The ideal candidate will have experience applying modern data science methods to Earth science or other spatial datasets, with strengths in machine learning, spatial statistics and geostatistics, GIS and geospatial analysis, scientific programming preferably in Python, data integration and visualization, and quantitative analysis of large or complex datasets. Experience with geothermal systems, subsurface geoscience, or natural-resource assessment is preferred. Strong quantitative problem-solving, scientific communication, and collaborative research skills are also preferred. Applicants must be U.S. citizens or Lawful Permanent Residents, be at least 18 years old, and have a minimum overall GPA of 3.50. All documents must be in English or include an official English translation.

How to apply

Go to the Zintellect opportunity page and click APPLY. Upload the required transcript, current resume/CV, and two educational or professional recommendations. Make sure all documents are in English or include an official English translation.

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