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separation and recovery methods for Gallium and Germanium. Major Duties/Responsibilities: Design and synthesize organic ligands, functionalization of resins, polymers. Design and execute adsorption based solid
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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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seeking a postdoctoral researcher with expertise in data management, workflow management, High Performance Computing (HPC), machine learning and Artificial Intelligence to enhance our capabilities in making
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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
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temperature. You will use and help refine techniques developed at ORNL that estimate shear strength based on the brittle-to-ductile transition, hot hardness testing, spherical indentation, and other new pending
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),. Familiarity with data analytics, machine learning, digital twin knowledge, or Python programming language. Knowledge of additive manufacturing, process physics, thermodynamics, and/or metallurgy to interpret
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Publish scientific results in peer-reviewed journals in a timely manner Participate in project planning and execution Maintain detailed and accurate records Acquire and analyze data in keeping with project
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) Fixed-effects panel models Matching methods (PSM, CEM, nearest-neighbor) Regression-based normalization Longitudinal and cross-sectional data analysis. Experience working with large administrative
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. Prepare peer-reviewed publications, technical reports, conference presentations, and sponsor deliverables based on research results. Deliver ORNL’s mission by aligning behaviors, priorities, and