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Position - USGS Data Science – Geothermal Energy Fellowship</div>
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Please apply through - <a href="https://findajob.agu.org/previewjob/8028475/usgs-data-science-geothermal-energy-fellowship/?Action=Preview#job-description" id="OWAee3686f1-e5d7-a873-3ea0-d36ad90ae458" class="OWAAutoLink">
USGS Data Science – Geothermal Energy Fellowship job with US Geological Survey | 8028475</a> (<a href="https://findajob.agu.org/previewjob/8028475/usgs-data-science-geothermal-energy-fellowship/?Action=Preview#job-description">https://findajob.agu.org/previewjob/8028475/usgs-data-science-geothermal-energy-fellowship/?Action=Preview#job-description</a>)</div>
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--- Posting description copied below ---</div>
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<span style="font-weight: 700;">Organization</span></div>
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U.S. Department of the Interior (DOI)</div>
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<span style="font-weight: 700;">Reference Code</span></div>
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DOI-USGS-2026-71</div>
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<span style="font-weight: 700;">How to Apply</span></div>
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<span style="font-weight: 700;"><i>To submit your application, scroll to the bottom of this opportunity and click APPLY.</i></span></div>
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A complete application consists of:</div>
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An application</li><li style="font-family: Calibri, Helvetica, sans-serif; font-size: 11pt; color: rgb(0, 0, 0); align-self: start;">
Transcript(s) – For this opportunity, an unofficial transcript or copy of the student academic records printed by the applicant or by academic advisors from internal institution systems may be submitted. Click
<a href="https://www.orau.org/internships-fellowships/documents/transcript-guidelines.pdf" target="_blank" id="OWA5fad11f1-04de-a518-1d72-383f5d44f40d" class="OWAAutoLink" style="color: rgb(13, 77, 181);">
<u>here</u></a> for detailed information about acceptable transcripts.</li><li style="font-family: Calibri, Helvetica, sans-serif; font-size: 11pt; color: rgb(0, 0, 0); align-self: start;">
A current resume/CV, including academic history, employment history, relevant experiences, and publication list</li><li style="font-family: Calibri, Helvetica, sans-serif; font-size: 11pt; color: rgb(0, 0, 0); align-self: start;">
Two educational or professional recommendations. At least one recommendation must be submitted in order for the mentor to view your application.</li></ul>
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All documents must be in English or include an official English translation.</div>
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<span style="font-weight: 700;">Application Deadline</span></div>
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11/17/2026 3:00:00 PM Eastern Time Zone</div>
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<span style="font-weight: 700;">Description</span></div>
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<span style="font-weight: 700;">*Applications will be reviewed on a rolling-basis.</span></div>
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<span style="font-weight: 700;">USGS Office/Lab and Location:</span> A research opportunity is currently available with the U.S. Geological Survey (USGS). This opportunity is with the USGS Conventional Geothermal Assessments Task within the Energy Resources
Program. Team-members are affiliated with the Geology, Minerals, Energy, and Geophysics Science Center, headquartered at Moffett Field, California, but with offices in each of the advertised locations.</div>
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The USGS mission is to monitor, analyze, and predict current and evolving dynamics of complex human and natural Earth-system interactions and to deliver actionable intelligence at scales and timeframes relevant to decision makers. As the Nation's largest water,
earth, and biological science and civilian mapping agency, USGS collects, monitors, analyzes, and provides science about natural resource conditions, issues, and problems. </div>
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<span style="font-weight: 700;">Research Project:</span> Under the guidance of a mentor, you will participate as part of an assessment team learning to compile and analyze spatial datasets using modern data-driven tools (e.g., machine learning) to map and estimate
conventional geothermal energy resources for the western United States (includes Alaska and Hawaii). You will have the opportunity to collaborate with a wide range of scientists across the USGS, possibly including geologists, geophysicists, GIS specialists,
volcanologists, machine learning experts, and geostatisticians. You will train with a team and will have the opportunity to expand your skills into adjacent and complementary toolkits. </div>
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<span style="font-weight: 700;">Learning Objectives: </span></div>
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Learn how conventional geothermal energy resources are identified, mapped, and estimated across the western United States, including Alaska and Hawaii.</li><li style="font-family: Calibri, Helvetica, sans-serif; font-size: 11pt; color: rgb(0, 0, 0); align-self: start;">
Develop experience compiling, managing, and analyzing large spatial datasets for energy-resource assessment.</li><li style="font-family: Calibri, Helvetica, sans-serif; font-size: 11pt; color: rgb(0, 0, 0); align-self: start;">
Build practical GIS and geospatial-analysis skills for integrating geologic, geophysical, volcanic, and other relevant datasets.</li><li style="font-family: Calibri, Helvetica, sans-serif; font-size: 11pt; color: rgb(0, 0, 0); align-self: start;">
Gain exposure to modern data-driven methods, including machine learning and geostatistics, for resource prediction and mapping.</li><li style="font-family: Calibri, Helvetica, sans-serif; font-size: 11pt; color: rgb(0, 0, 0); align-self: start;">
Learn how interdisciplinary scientific evidence is combined to characterize geothermal potential and uncertainty.</li><li style="font-family: Calibri, Helvetica, sans-serif; font-size: 11pt; color: rgb(0, 0, 0); align-self: start;">
Develop collaborative research skills with geologists, geophysicists, GIS specialists, volcanologists, machine-learning experts, and geostatisticians across the USGS.</li><li style="font-family: Calibri, Helvetica, sans-serif; font-size: 11pt; color: rgb(0, 0, 0); align-self: start;">
Expand technical capacity by exploring complementary analytical tools and adjacent scientific disciplines within a team-based research environment.</li></ul>
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<span style="font-weight: 700;">Anticipated Appointment Start Date: 2026. </span>
Start date is flexible and will depend on a variety of factors.</div>
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<span style="font-weight: 700;">Appointment Length: </span>The appointment will initially be for three months, but may be renewed upon recommendation of DOI and is contingent on the availability of funds.</div>
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<span style="font-weight: 700;">Level of Participation: </span>The appointment is full time.</div>
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<span style="font-weight: 700;">Participant Stipend:</span> Stipend rates may vary based on numerous factors, including opportunity, location, education, and experience. The following are the stipend rates for applicants with a doctoral degree.
<span style="font-weight: 700;">Note that the listed annual stipend range corresponds to the allowable locations (Moffett Field, CA [$134,280]; Denver, CO [$119,756]; Portland, Oregon [$115,729]; Bozeman, MT [$107,446]).</span> If you are interviewed, you can
inquire about the exact stipend rate at that time.</div>
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<span style="font-weight: 700;">Citizenship Requirements: </span>This opportunity is available to U.S. citizens and Lawful Permanent Residents (LPR) only.</div>
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<span style="font-weight: 700;">ORISE Information: </span>This program, administered by ORAU through its contract with the U.S. Department of Energy (DOE) to manage the Oak Ridge Institute for Science and Education (ORISE), was established through an interagency
agreement between DOE and USGS. Participants do not become employees of USGS, DOE or the program administrator, and there are no employment-related benefits. Proof of health insurance is required for participation in this program. Health insurance can be obtained
through ORISE.</div>
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<span style="font-weight: 700;">Qualifications</span></div>
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The qualified candidate should have received or be currently pursuing a master's or doctoral degree in one of the relevant fields (geoscience, data science, computer science, statistics, geography, engineering, or a related field). </div>
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A minimum of holding a master's degree is required, but a doctoral degree is preferred.</div>
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<span style="font-weight: 700;">Preferred skills:</span></div>
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The ideal applicant will have experience applying modern data science methods to Earth science or other spatial datasets, with strengths in one or more of the following areas: 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.</li><li style="font-family: Calibri, Helvetica, sans-serif; font-size: 11pt; color: rgb(0, 0, 0); align-self: start;">
Experience with geothermal systems, subsurface geoscience, or natural-resource assessment is preferred.</li><li style="font-family: Calibri, Helvetica, sans-serif; font-size: 11pt; color: rgb(0, 0, 0); align-self: start;">
Strong quantitative problem-solving, scientific communication, and collaborative research skills are also preferred.</li></ul>
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<span style="font-weight: 700;">Stipend</span></div>
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$107,400.00 – $134,280.00 Yearly</div>
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<span style="font-weight: 700;">Eligibility Requirements</span></div>
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<span style="font-weight: 700;" role="presentation">Citizenship: </span>LPR or U.S. Citizen</li><li style="font-family: Calibri, Helvetica, sans-serif; font-size: 11pt; color: rgb(0, 0, 0); text-indent: 0px; align-self: start;">
<span style="font-weight: 700;" role="presentation">Degree:</span> Master's Degree or Doctoral Degree.</li><li style="font-family: Calibri, Helvetica, sans-serif; font-size: 11pt; color: rgb(0, 0, 0); text-indent: 0px; align-self: start;">
<span style="font-weight: 700;" role="presentation">Minimum Overall GPA:</span> 3.50</li><li style="font-family: Calibri, Helvetica, sans-serif; font-size: 11pt; color: rgb(0, 0, 0); text-indent: 0px; align-self: start;">
<span style="font-weight: 700;" role="presentation">Age:</span> Must be 18 years of age</li></ul>
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*****</div>
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Stanley Mordensky</div>
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Research Geologist, U.S. Geological Survey</div>
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