The New AFERA Framework in Action: AI-Based Digital Twin for Data Center Thermal Management and Optimization

Oak Ridge Institute for Science and Education; Morgantown (WV); Sur place; USD 41 000 - 78 000; Plein temps

Résumé du poste

Oak Ridge Institute for Science and Education (ORISE) administers a student researcher opportunity with the National Energy Technology Laboratory (NETL) in Morgantown, WV. The project focuses on applying AI, ML and reduced-order modeling to develop a digital twin for NETL's Joule 3.0 MDC under the AFERA framework.

Participants gain hands-on experience, mentors, and an opportunity to contribute to scholarly publications, with stipends of 788 to 1499 USD per week depending on status.

Qualifications

• Familiarity with AI/ML, physics-informed neural networks, or ROM.
• Some experience with programming tools (Python, MATLAB, C/C++).
• Familiarity with ML: predictive modeling, anomaly detection, supervised learning, deep learning, feature engineering, hyperparameter tuning, model evaluation.
• Technical communication skills.

Responsabilités

• Gain familiarity with the AFERA digital engineering approach.
• Identify advantages of the AFERA approach to accelerate research.
• Synthesize and analyze diverse data streams and performance.
• Collaborate with research scientists.

Connaissances

AI/ML basics

Physics-informed ML

Reduced-order modeling (ROM)

Formation

Undergrad or Grad student status

GPA 2.5/4.0+

Outils

Python

MATLAB

C++

C

Description du poste

Organization

National Energy Technology Laboratory (NETL)

Reference Code

NETL-PIP-2026-Guenther

Description

The National Energy Technology Laboratory's (NETL's) record of success has been built on understanding the future of energy and the technologies required to make that future possible. We’ve long touted our success in developing the technologies that took on acid rain in the 1970s and mercury in the early 2000s.

Program Goals

• Develop skills and knowledge in their field of study
• Engage with new areas of basic and applied research
• Transition classroom theory into hands-on experience
• Network with world-class scientists
• Exchange ideas and skills with the Laboratory community
• Use state-of-the-art equipment
• Contribute to answers for today's pressing scientific questions
• Collaborate with the broader scientific and technical communities

Project Details

Through the Oak Ridge Institute for Science and Education (ORISE), this posting seeks a student researcher, recent Bachelor's graduate, or recent Master's graduate to engage in projects with the Research Innovation Center (RIC) at the National Energy Technology Laboratory (NETL) in the area of LDRD under the mentorship of Chris Guenther. This project will be hosted at the NETL Morgantown, WV campus. The U.S. Department of Energy (DOE) is driving a transformative initiative to integrate Artificial Intelligence (AI) into scientific discovery, leveraging its capacity to accelerate complex physics-based modeling and analyze vast datasets at unprecedented speeds. Agentic AI further enhances this by enabling autonomous reasoning and execution of research objectives, fundamentally redefining research paradigms. The larger, over-arching project focuses on the Applied Federated Energy Research Accelerator (AFERA), a novel framework for end-to-end applied energy research integrating Agentic AI, Applied Energy Solvers, Digital Twins, and Control & Automation. To demonstrate AFERA's feasibility, an initial use case involves developing a comprehensive digital twin for NETL’s Joule 3.0 Modular Data Center (MDC). The MDC, with its real-time and historical operational data and well-defined infrastructure for high-fidelity physics-based computer simulations, is an ideal testbed platform. Models of the MDC will be simplified into static and hybrid reduced-order models (ROMs) to create an integrated, predictive MDC Digital Twin. This effort will showcase the ability of the new AFERA framework, informed by AI, to synthesize diverse data streams from process data to commercial/in-house simulation outputs, constructing precise MDC models for a dynamic digital twin. As a participant on this project, you will be introduced to AFERA and gain familiarity with its function, processes, and impact, accelerating scientific research. This validation will confirm AFERA's broader applicability, catalyzing research acceleration in other strategic DOE areas.

The Overall Objectives Of This Project Are

• Gain familiarity with the AFERA digital engineering approach
• Identify advantages of the AFERA digital engineering approach to accelerate research
• Synthesize and analyze diverse data streams and performance
• Collaborate with research scientists

Stipend

• $788 per week for undergraduate students
• $1225.50 per week for recent Bachelor's graduates
• $1499 per week for graduate students and recent Master's graduates

Program Requirements

To document the effectiveness of the program, participants are required to submit a pre-appointment and post-appointment survey, as well as a reflection on their appointment experience when they renew or end their appointment. The reflection should summarize their project(s), additional activities, and overall experience. Details are provided as the appointment end date approaches. Participants may also have the opportunity to contribute to manuscripts, journal articles, book chapters, conference presentations, posters, patents, and other publications as a part of their appointment. Such achievements should also be reported to ORISE; additional details are provided after an offer has been accepted. The National Energy Technology Laboratory (NETL), part of the U.S. Department of Energy (DOE) national laboratory system, is owned and operated by the DOE. NETL supports the DOE mission to advance the energy security of the United States. This is an educational opportunity offered by NETL and administered by the Oak Ridge Institute for Science and Education. Participants in the program are not considered employees of NETL, DOE, the program administrator, or any other office or agency.

Qualifications

• Familiarity with artificial intelligence, machine learning, physics-informed neural networks, or reduced-order modeling (ROM)
• Some experience with various programming tools (Python, MATLAB, C++, C)
• Some familiarity with machine learning: predictive modeling, anomaly detection, supervised learning, deep learning, feature engineering, hyperparameter tuning, model evaluation
• Technical communication skills

To Be Eligible For This Opportunity, You Must

• Have one of the following academic statuses
  • An undergraduate student*1 in good standing at a regionally accredited college/university*2
  • A recent Bachelor's degree graduate*1 who has received their Bachelor's degree from a regionally accredited college/university*2 within the last 60 months before the intended appointment start date
  • A graduate student in good standing at a regionally accredited college/university
  • A recent Master's degree graduate who has received their Master's degree from a regionally accredited college/university within the last 60 months before the intended appointment start date
• Have an overall GPA of 2.5/4.0 or higher
• Be at least 18 years of age at the time of application
• Provide confirmation of coverage under a health insurance plan prior to the beginning of the internship
• 1 Soon-to-be Associate's degree graduates are eligible to apply if enrolled as a student at time of application.
• 2 Students and recent Bachelor's degree graduates from accredited Community Colleges and Technical Schools are encouraged to apply.

Point of Contact

Jordan

Eligibility Requirements

• Degree: Associate's Degree, Bachelor's Degree, Master's Degree, or Doctoral Degree.
• Minimum Overall GPA: 2.50
• Discipline(s):
  • Chemistry and Materials Sciences
  • Analytical Chemistry
  • Bio-inorganic Chemistry
  • Bio-organic Chemistry
  • Biophysical Chemistry
  • Chemistry (General)
  • Environmental Chemistry
  • Inorganic Chemistry
  • Materials Sciences
  • Organic Chemistry
  • Physical Chemistry
  • Polymer Chemistry
  • Theoretical Chemistry
  • Communications and Graphics Design (2 )
  • Computer, Information, and Data Sciences (17 )
  • Earth and Geosciences (21 )
  • Engineering (29 )
  • Environmental and Marine Sciences (14 )
  • Life Health and Medical Sciences (51 )
  • Mathematics and Statistics (11 )
  • Physics (16 )
  • Science & Engineering-related (2 )
  • Social and Behavioral Sciences (29 )
  • Age: Must be 18 years of age

Affirmation

I Certify At The Time Of Application That I Meet At Least One Of The Following Academic Status Eligibility Criteria, At a Regionally Accredited Academic Institution

• I am currently pursuing an undergraduate degree.
• I received a Bachelor's degree no more than 60 months before the intended appointment start date.
• I am currently pursuing a Master's degree.
• I received a Master’s degree no more than 60 months before the intended appointment start date.
• I am currently pursuing a doctoral degree.