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machine learning and Bayesian calibration methods to enable multi-scale, multi-physics model development. Complete simulation verification, model validation, uncertainty quantification, and documentation
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(ORNL) is seeking a highly motivated Postdoctoral Researcher with expertise in artificial intelligence and machine learning (AI/ML), remote sensing, Earth and environmental sciences, and the analysis
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scientific domain and knowledge of high performance and quantum computing and scalable data analytics and/or deep learning Preferred Qualifications: Qualified candidates should have demonstrated management
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, computer science, or engineering within the past 5 years. Previous theoretical and/or computational research experience in tensor networks, Monte Carlo, machine learning or a related field Proficiency in quantum
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analytics, including correlation analysis and machine learning techniques. Preferred Qualifications: Experience with microstructure characterization techniques (SEM, EBSD, TEM, XRD). Experience in mechanical
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management, and other needs for DOE, DOW, and DHS sponsors. This is an early-career position intended for a candidate who will work alongside and learn from experienced staff while independently executing
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. Demonstrate proficiency in MS Word, MS Outlook, MS Excel, and PowerPoint. Must have ability to learn quickly and adapt to rapid changes. Excellent interpersonal and verbal and written communication skills
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machine learning algorithms. This position resides in the Manufacturing Systems Analytics (MSA) Group in the Manufacturing Science Division (MSD), Energy Science and Technology Directorate (ESTD), at Oak
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machine learning algorithms. This position resides in the Manufacturing Systems Analytics (MSA) Group in the Manufacturing Science Division (MSD), Energy Science and Technology Directorate (ESTD), at Oak
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solutions, and making sound decisions without requiring extensive day-to-day supervision. Radiochemistry and/or nuclear chemistry experience is preferred but not required; willingness and ability to learn