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expected to contribute to the development and application of advanced manufacturing simulations, and machine learning (ML) models relevant to additive manufacturing, virtual manufacturing, material
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, enabling manual and automated adversarial testing at scale. Build and integrate AI-on-AI testing infrastructures, where AI models can actively challenge each other in adversarial contexts to detect
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Learning skills. This position resides in the AI Operations Program office within the Application Development Division of the Information Technology Services Directorate. Our AI/ML models are heavily
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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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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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Requisition Id 15751 Overview: The Advanced Computing in Health Sciences (ACH) section at the Oak Ridge National Laboratory is seeking qualified applicants for a Machine Learning Engineer position
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needs. By leveraging advanced simulations, machine learning, and data-driven insights, the group enables more effective operations aligned with evolving energy demands. The group also develops hydrologic
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platforms and autonomous systems, to characterizing global population risk with increasing spatiotemporal clarity, to designing GeoAI models for supercomputer-scale applications, geospatial science at ORNL is
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in multiscale and multifidelity simulation techniques (ab initio methods at different fidelity, machine learning tight-binding, machine learning force fields, phase-field modeling, and/or kinetic monte