772 machine-learning-"https:"-"https:"-"https:" Postdoctoral positions in United States
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National Energy Technology Laboratory (NETL) | Morgantown, West Virginia | United States | about 2 months ago
permeability of fluid flow through hydrate-bearing sediments, • High resolution visualizations of hydrate distributions and fluid migration in porous media under in situ conditions, and • Machine learning
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National Energy Technology Laboratory (NETL) | Morgantown, West Virginia | United States | 23 days ago
The ideal candidate would have some, but not necessarily all, knowledge of and skills in: Familiarity with artificial intelligence, machine learning, physics-informed neural networks, or reduced-order
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National Energy Technology Laboratory (NETL) | Morgantown, West Virginia | United States | about 12 hours ago
migration in porous media under in situ conditions, and • Machine learning application to gas hydrate system to develop efficient key parameter estimation tools and large-scale 3D geologic model for gas
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),. Familiarity with data analytics, machine learning, digital twin knowledge, or Python programming language. Knowledge of additive manufacturing, process physics, thermodynamics, and/or metallurgy to interpret
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learning, or optimization Strong programming skills in Python and experience with scientific computing and machine-learning libraries Ability to work across experimental, robotic, and computational systems
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deep expertise in modern machine learning and a strong record of research accomplishment who are excited to advance foundation models, agentic systems, and new AI approaches for high-impact scientific
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are seeking a highly motivated researcher with a strong background and interest in machine learning and artificial intelligence. The position focuses on the development and application of advanced deep learning
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methylation, chromatin accessibility), and clinical data. · Develop, apply, and benchmark machine learning and statistical models for subtype discovery, classification, and outcome prediction. · Contribute
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on type, size, location of data centers in the US, their electricity and water demand, carbon emissions; exposure to air pollution. ● Develop and/or apply methods for causal inference and machine learning
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. Experience with developing machine-learning surrogates for structure-property relationship, generative AI models, material representations, machine learning force-fields (especially extensions to spinful