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Field
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producing well-structured, user-friendly, reproducible research code (e.g., packages, documented pipelines, open-source contributions, or similar). Written and oral communication skills, with the ability
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National Energy Technology Laboratory (NETL) | Pittsburgh, Pennsylvania | United States | about 2 hours ago
Organization National Energy Technology Laboratory (NETL) Reference Code NETL-Postdoc-2026-Goodman How to Apply A complete application consists of: An application, including academic history, work
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beyond traditional error estimators, creating physics-based adaptation algorithms that intelligently predict where refinement will be most beneficial for smarter, more efficient simulations. We seek
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environmental science is of supreme importance. Students entering the science classroom bring well-developed intuitive frameworks that help them understand, explain, and predict the world around them. These
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systems (proteins, enzymes, membranes, and complexes) Integrate AI/ML approaches with physics-based simulations to accelerate discovery and improve predictive fidelity Contribute to cross-scale modeling
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mechanobiological models of bone healing will help create a robust model, able to predict long term surgical outcomes in patient specific cases. The results of the validated model will provide insight
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at the intersection of active transportation safety and AI (e.g., near-miss detection, predictive crash risk, multimodal exposure estimation). · Design, implement, and validate AI pipelines (computer vision
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and integration of multimodal neuroimaging, behavioral and clinical data, and building large-scale deep learning models for multimodal neuroimaging datasets to construct predictive network models in
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Expertise in machine learning, including building and deploying prediction models Strong data science coding skills in programs and languages such as Python, R, Stata, and SQL Experience with research in
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campus as arts and sciences. The fellow will lead the development and validation of imaging-based models to predict patient response to cancer treatment (80%) and will manage the unit’s AI/ML core