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residency requirement, you will be required to obtain a PIV credential to maintain employment. Postdocs: Applicants cannot have received their Ph.D. more than five years prior to the date of application and
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rotor and suspension behavior across design and test environments. This role requires both deep technical expertise and strategic leadership in extending modeling capabilities through the modification
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Write software to support cutting edge research and facilitate Proof of Concept demonstrations Implement, evaluate, and enhance machine learning pipelines for cybersecurity applications Basic
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Requisition Id 15885 Overview: We are seeking a Postdoctoral Research Associate – Simulation and Machine Learning for Composite Manufacturing who will focus on developing physics-based simulation
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strengths in any of these areas — quantitative imaging, modeling/transport science, machine learning, or scientific programming — are encouraged to apply. Major Duties/Responsibilities: Lead energy‑storage
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include data compression and reconstruction, data movement, data assimilation, surrogate model design, and machine learning algorithms. The position comes with a travel allowance and access to advanced
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computational physics, computational materials, and machine learning and artificial intelligence, using the DOE’s leadership class computing facilities. This position will utilize methods such as finite elements
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management, workflow management, High Performance Computing (HPC), machine learning and Artificial Intelligence to enhance our capabilities in making AI-ready scientific data. As a postdoctoral fellow at ORNL
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to numerical methods for kinetic equations. Mathematical topics of interest include high-dimensional approximation, closure models, machine learning models, hybrid methods, structure preserving methods, and
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to Computational Methods for Data Reduction. Topics include data compression and reconstruction, data movement, data assimilation, surrogate model design, and machine learning algorithms. The position comes with a