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and numerical algorithms for modeling and simulation of nuclear systems. Computational Nuclear Engineers within the RTHPCM group will work with group, section, and division members and external
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-class S&T products for sensitive national security missions. The selected candidate will support research efforts in signal processing and analysis, with an emphasis on the development of novel algorithms
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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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-flows. Basic Qualifications: PhD in mathematics, computer science, engineering, or related field earned within the last 5 years. Preferred Qualifications: Experience with mesh generation/CFD applications
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length scales Develop machine learning algorithms to support process optimization, predictive modeling, and intelligent manufacturing control Integrate simulation tools with in-situ sensor data from
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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
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Postdoctoral Research Associate who will focus on creating innovative artificial intelligence algorithms for the trusted visualization of large-scale 3D scientific data. This position resides in the Data
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Description Overview: We are seeking a Postdoctoral Research Associate who will focus on creating innovative uncertainty quantification and visualization algorithms that enable trusted visual representation and
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computing resources. The MMD group is responsible for the design and development of numerical algorithms and analysis necessary for simulating and understanding complex, multi-scale systems. The group is part
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and resilience across heterogeneous computational resources while addressing workflow requirements for scientific applications. Validate distributed intelligence algorithms at scale on ORNL's