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data and develop data-driven methods for predicting land loss and ecosystem transitions in wetland-rich landscapes of the Gulf Coast with a focus on coastal Louisiana. This candidate will directly
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for Computational Sciences. They will collaborate with leading computer and computational scientists at ORNL and external collaborators in the development and application of new computational techniques specifically
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interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service. Basic Qualifications: A PhD in Earth and Environmental Sciences, Ecology, Biosciences, Botany, Geosciences, or a related
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Application-driven Composable Distributed Storage. The candidate will be able to make research contributions in understanding and efficient use of distributed data storage and I/O subsystems for High
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time-of-flight secondary ion mass spectrometry (ToF-SIMS), scanning electron microscopy (SEM), and X-ray diffraction (XRD). Experience in data reduction of big spectroscopy, mass spectrometry, and image
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to research proceedings and publications Prepare technical reports Deliver briefings to stakeholders Basic Qualifications: A PhD in Chemical Engineering, Mechanical Engineering, Physics, Materials Science
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measure success. Basic Qualifications: A PhD in Chemistry, Physics, Materials Science or a related field completed within the last 5 years. Preferred Qualifications: Experience with interface battery
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evolution, phase stress, and defect evolution using advanced data analysis tools. Perform alloy fabrication and processing (e.g., arc melting, heat treatment) and relate processing to performance. Apply
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opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: PhD in chemical engineering, chemistry, mechanical engineering, civil
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strengths in high-performance computing, system architecture, and data analytics with applications in a large variety of science domains. NCCS is home to some of the fastest supercomputers and storage systems