23 construction-"https:"-"https:"-"https:" Postdoctoral positions at Oak Ridge National Laboratory
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. Knowledge of fiber manufacturing processes and structure-property relationships is a plus. Strong analytical and problem-solving skills. Excellent written and verbal communication abilities. Experience in
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Confidential Computing and Secure Multi-tenancy. The candidate will be able to make research contributions in areas of system software architectures to support secure computing enclaves on large scale HPC and
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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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applications. This role offers unparalleled access to ORNL’s world-leading computational resources, including the Frontier supercomputer, and the chance to make meaningful contributions to DOE's mission-critical
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technologies and provides assurance to build knowledge and impact in novel, crosscut-science outcomes. The candidate will be a postdoctoral researcher within the Multiscale Materials (MsM) group of the Advanced
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, devices, and networked systems. It develops community applications, data assets, and technologies and provides assurance to build knowledge and impact in novel, crosscut-science outcomes. The selected
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the necessary chemistry and processing modifications to meet target alloy properties. Apply advanced characterization and modeling techniques and make fundamental contributions to the field. Interact with other
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modeling techniques and make fundamental contributions to the field. Interact with other researchers, technicians, and students to shape and drive the research agenda. Present and report research results and
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, including automated QC and uncertainty-aware learning from sparse/noisy measurements Build hybrid mechanistic–AI models linking traits to photosynthesis, stomata, hydraulics, and respiration across
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and software tools for visualizing and analyzing materials characterization data Develop novel, data-driven materials characterization workflows Advance understanding of process-structure-property