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to Computational Fluid Dynamics. Mathematical topics of interest include structure-preserving finite element methods, advanced solver strategies, multi-fluid systems, surrogate modeling, machine learning, and
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limited supervision, operate a variety of machine tools to inspect, calibrate, or produce precision parts and instruments. You will be responsible for applying knowledge of mechanics, mathematics, metal
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analytics that enhance and evolve business operations and scientific decision-making capability and related activities at ORNL.Qualified applicants will have a solid foundation of Generative AI and Machine
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Qualifications: Advanced degree (MS or PhD) in Computer Science, Data Science, Geospatial Science (GIS/remote sensing), Electrical/Computer Engineering, or a closely related discipline. Minimum of 10–12 years
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organizing workshops, reports, position papers and detailed roadmaps to foster cross-agency engagement and outline utility-scale roadmaps for the QHPC initiative. Qualifications: PhD in Quantum Computing
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). Experience with stereo imagery, LIDAR, and other 3D sensing capabilities. Proficient in a Linux OS environment. Familiarity with the basics of machine learning and high-performance computing (HPC). Experience
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respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: PhD degree and 4 years of relevant postgraduate experience or a MS degree with 10 years
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fabrication Machine learning (ML)/artificial intelligence (AI) coursework Experience with AI/ML libraries (TensorFlow, PyTorch) Special Requirements: Work involves various physical requirements and working
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optical systems, thermal imaging, pyrometry, spectroscopy, high speed imaging or acoustic sensing. Familiarity with data analytics, machine learning, or signal processing. Knowledge of metal additive
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development teams Basic Qualifications: A Bachelor's degree in Computer Science, Electrical or Computer Engineering, or other field relevant to the job duties. Competency in Python and C++ programming Ability