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National Renewable Energy Laboratory (NREL)

Prediction of Mechanical Behaviors of Heat-Resistant Structural Alloys Using Digital Twin Technologies National Energy Technology Laboratory (NETL) in United States

Degree Level

Postdoc

Field of study

Computer Science

Funding

Post-doctoral stipend is $8455 per month; monthly stipend is commensurate with educational level and experience.

Deadline

Dec 31, 2026

Country flag

Country

United States

University

National Renewable Energy Laboratory (NREL)

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Keywords

Computer Science
Chemistry
Molecular Dynamics
Digital Twin Technology
Microstructure Evolution
Density Functional Theory
High-entropy Alloy
Physics
Finite Element Analysi
Computational Materials Science
ML

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About this position

This postdoctoral research opportunity at the National Energy Technology Laboratory (NETL) is centered on predicting the long-term mechanical behavior of heat-resistant structural alloys using digital twin technologies. The project is hosted by NETL’s Albany, Oregon campus and is conducted off-site/virtually under the mentorship of Michael Gao within the Research Innovation Center (RIC) in the Power, Fuels & Chemicals area.

The researcher will work on developing predictive capabilities for alloys exposed to fatigue, creep, and creep-fatigue interaction under industrial operating conditions. Materials of interest include brazed aluminum heat exchangers, nickel-based superalloys, heat-resistant steels, and high-entropy alloys. The project emphasizes how microstructural features and defects—such as precipitates, vacancies, interstitials, stacking faults, twins, dislocations, grain boundaries, and surfaces—affect long-term performance and lifetime.

The appointment is highly interdisciplinary and combines computational materials science with advanced modeling and data-driven methods. The participant will explore reliable and computationally efficient frameworks for predicting creep and fatigue behavior while accounting for microstructural evolution. Research approaches include physics-informed and deep learning-based digital twin methods, density functional theory, machine learning interatomic potentials, molecular dynamics, Monte Carlo simulations, and finite element methods.

The selected researcher will gain experience in multi-scale computational modeling and machine learning applied to mechanical behavior of structural alloys, while interacting with researchers from other national laboratories and industry. NETL’s postdoctoral program also provides mentorship from principal investigators and leads in a research environment focused on energy-related science and technology.

Funding details

Post-doctoral stipend is $8455 per month; monthly stipend is commensurate with educational level and experience.

What's required

Applicants must have received a doctoral degree within the last five years or be currently enrolled in a doctoral degree program and complete the degree before the appointment start date. The ideal candidate will have a Ph.D. in Materials Science, Physics, or a closely related discipline; research experience in dislocation modeling and simulation and density functional theory calculations; proficiency in artificial intelligence, machine learning, and/or machine learning interatomic potential; previous peer-reviewed publications; programming skills; and the ability to conduct independent research in a multi-disciplinary team. All documents must be in English or include an official English translation.

How to apply

Submit a complete application in Zintellect with academic history, work history, honors/awards, goals and experience statement, transcripts, resume or CV, and contact information for at least two recommenders. If you want to speak with the hosting researcher, first submit the application and then email [email protected]; questions about the application process go to [email protected].

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