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, finite volume, and machine learning to solve challenging real-world problems related to structural materials and advanced manufacturing processes. The successful candidate will have experience with
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compliance, reproducibility, and interoperability across scientific domains. By improving data readiness processes, this role will amplify the potential of AI-driven discovery in areas such as high energy
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workplace – in how we treat one another, work together, and measure success. Basic Qualifications: A PhD in evolutionary biology, plant biology, genomics, bioinformatics, mathematics, statistics, computer
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(ORNL). This position will focus on the development, characterization, and application of engineered nanoparticles for medical isotope systems, including technologies relevant to isotope processing
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data science to develop new methodologies for assessing and improving the quality of components fabricated using advanced manufacturing processes. This position resides in the Manufacturing Systems
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process-based modeling of hydrologic or land surface processes. The WSMG group develops advanced surface/subsurface integrated hydrologic and reactive transport models, works with other groups to compare
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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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enrichment devices for processing uranium-bearing and stable isotope compounds. The Mechanical Systems Modeling Group applies first-principles physics and empirically informed methods to advance
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to contribute to development of alloys with desirable advances in mechanical properties, thermal/electrical properties, and processability. A background in solidification processing, high pressure die casting
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and image data processing. Specific knowledge related to neural network design, training, and optimization is required. You will be joining a group with core expertise in sensor data analytics from