USGS Water Use Estimation for Data Center Industry

Oak Ridge Institute for Science and Education; Evanston (IL); On-site; USD 60,000 - 70,000; Full time

Job summary

Oak Ridge Institute for Science and Education invites doctoral researchers to participate in a mentored learning opportunity with the U.S. Geological Survey in Evanston, Illinois.

The focus is on advancing methods to estimate direct data center water use and developing a regional machine learning modeling framework under evolving AI and cloud computing contexts. The appointment is full-time for two years, with a flexible start date and a stipend based on opportunity, location, education, and

Qualifications

• PhD in Computer, Information, and Data Sciences, Earth and Geosciences, or Environmental/Marine Sciences.
• Doctoral degree must be recent (within last 3 years).

Responsibilities

• Conduct research synthesizing structured and unstructured datasets to estimate direct data center water use.
• Develop and evaluate a regional ML modeling framework integrating facility characteristics, cooling tech, and environmental conditions.
• Communicate findings clearly and contribute to foundational science for national assessments.

Skills

Motivated learner

Education

Doctoral degree

Job description

Reference Code

DOI-USGS-2026-70

Application Deadline

10/15/2026 3:00:00 PM Eastern Time Zone

USGS Office/Lab and Location

U.S. Geological Survey (USGS) located in Evanston, Illinois. This is not a remote opportunity.

Description

• Applications will be reviewed on a rolling-basis.

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.

Research Project

Rapid expansion of data centers to support artificial intelligence and cloud computing, accelerated by federal policy (Executive Order 14179), has created an emerging water-use category with important implications for water resources and infrastructure. Consistent with the USGS mission to provide impartial scientific information about the Nation’s water resources, this research participation opportunity offers a mentored learning experience focused on advancing methods to estimate direct data center water use under varying climatic, technological, and operational conditions. You will conduct research that synthesizes publicly available information (for example, utility reports, sustainability disclosures, and cooling technology specifications) and other compiled datasets to explore uncertainties in reported water use and to develop a pilot, regionally scalable modeling framework. The primary focus of this appointment is to provide hands‑on training in data synthesis, uncertainty evaluation, and predictive modeling while contributing to foundational science that may inform future national assessments.

Learning Objectives

• Gain experience compiling and comparing structured and unstructured datasets to identify key uncertainties in estimating direct data center water use, including development of reproducible data extraction and documentation approaches; and
• Develop and evaluate a regional machine learning modeling framework that integrates facility characteristics, cooling technologies, and environmental conditions to explore water‑use estimates under multiple growth and climate scenarios, while strengthening skills in feature engineering, model evaluation, uncertainty analysis, and clear scientific communication.

Mentor

The mentor for this opportunity is Guoxiang Yang ([e-mail]). If you have questions about the nature of the research please contact the mentor(s).

Anticipated Appointment Start Date

October 19, 2026. Start date is flexible and will depend on a variety of factors.

Appointment Length

The appointment will initially be for two years, but may be renewed upon recommendation of DOI and is contingent on the availability of funds.

Level of Participation

Full time.

Participant Stipend

Stipend rates may vary based on numerous factors, including opportunity, location, education, and experience. If you are interviewed, you can inquire about the exact stipend rate at that time and if selected, your appointment offer will include the monthly stipend rate.

Citizenship Requirements

This opportunity is available to U.S. citizens only.

ORISE Information

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.

Questions

If you have questions about the application process please email [e-mail] and include the reference code for this opportunity.

Qualifications

The qualified candidate should have received a doctoral degree in one of the relevant fields. Degree must have been received within the past three years.

Preferred Skills

• The ideal candidate is highly motivated, eager and capable of learning new things, and able to perform both independently as well as with a team.

Point of Contact

Rachel

Eligibility Requirements

• Citizenship: U.S. Citizen Only
• Degree: Doctoral Degree received within the last 36 month(s).
• Discipline(s):
  • Computer, Information, and Data Sciences (Data Science)
  • Earth and Geosciences (2 )
    • Engineering (1 )
      • Environmental and Marine Sciences (1 )