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and aspects related to safety and best practices. The candidate will make extensive use of state-of-the-art imaging, spectroscopy (Raman, electron microscopy, infrared, etc.) and scattering methods
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Postdoctoral Research Associate - Multifunctional Equipment Integration Energy Conversion Technology
research assignments related to energy conversion systems including: Prototype development Material synthesis and analysis Performance testing Analysis of results Preparing research publications Prepare
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, quantify nonlinear interactions, and advance scientific understanding of coastal ecosystem resilience. Curate and develop reproducible AI-ready datasets, computational workflows, and research software
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funding. Communicate research findings through technical reports, conference presentations, and timely publications in peer-reviewed journals. Prepare invention disclosures and contribute to patent
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, conduct experimental campaigns, perform materials synthesis and analysis, sub-component fabrication, process optimization and integration, and prepare technical documents and research publications. Present
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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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. Prepare peer-reviewed publications, technical reports, conference presentations, and sponsor deliverables based on research results. Deliver ORNL’s mission by aligning behaviors, priorities, and
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simulation tasks. Develop and maintain HPC-ready software workflows for distributed training, large-scale inference, scalable data ingestion, and data management on leadership-class computing systems and
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to post-process characterization. This environment enables the creation of high-fidelity digital twins and AI-ready datasets that support real-time monitoring, predictive modeling, and process optimization