7 model-predictive Postdoctoral positions at National Energy Technology Laboratory (NETL)
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National Energy Technology Laboratory (NETL) | Albany, New York | United States | about 23 hours ago
will engage in multiscale modeling and machine learning to develop reliable, efficient framework for predicting long-term creep and fatigue behaviors of heat-resistant structural alloys considering
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National Energy Technology Laboratory (NETL) | Morgantown, West Virginia | United States | 25 days ago
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
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National Energy Technology Laboratory (NETL) | Morgantown, West Virginia | United States | about 2 months ago
systems that will benefit the development of models and methods for predicting the behavior of gas hydrates in their natural environment under natural conditions and production scenarios. RIC supports major
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National Energy Technology Laboratory (NETL) | Morgantown, West Virginia | United States | about 23 hours ago
Development Program to obtain pertinent, high-quality information on natural gas hydrates systems that will benefit the development of models and methods for predicting the behavior of gas hydrates in
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National Energy Technology Laboratory (NETL) | Morgantown, West Virginia | United States | 25 days ago
accelerate scientific discovery in strategic energy research. As a postdoctoral researcher, you will investigate rich real-time and historical operational data, to explore a predictive digital twin
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National Energy Technology Laboratory (NETL) | Morgantown, West Virginia | United States | 25 days ago
a dynamic, predictive digital twin. You will investigate the feasibility and accelerated research capabilities of the AFERA approach and collaborate with other researchers in AI-based digital twin
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National Energy Technology Laboratory (NETL) | Pittsburgh, Pennsylvania | United States | about 23 hours ago
lab results to predictive reservoir models. Through this project, the participant will learn about hands on lab experience, modeling, and presenting and publishing results. The participant will: (1