71 parallel-processing-"LCC-CNRS" Postdoctoral positions at Oak Ridge National Laboratory
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in delivering the intended residential energy cost and other household direct benefits. Data collection, processing/curation, and analysis. Development and implementation of econometric analysis (e.g
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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 Ceramic Engineering, Materials Science and Engineering, Mechanics
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in the areas of Hydrological and Earth System Modeling and Artificial Intelligence (AI). The successful candidate will have a strong background in computational science, data analysis, and process
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characterization of HPC and scientific AI applications or libraries on multi-tier HPC storage systems. Design and evaluation of approaches for time-sensitive or data-intensive processing of data originating
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institutional clusters. Write robust Linux bash scripts and job submission scripts for SLURM and PBS environments, including multi-node GPU/CPU workflows, monitoring, restart, and post-processing pipelines
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, Integrity, Teamwork, Safety, and Service. Promote equal opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: A Ph.D. degree
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data science to develop new methodologies for assessing and improving the quality of components fabricated using advanced manufacturing processes. This position resides in the Manufacturing Systems
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system dynamic and transient simulations. Integrate post-processing measures for simulations to help with automation. Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our
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, Integrity, Teamwork, Safety, and Service. Promote equal opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success Basic Qualifications: A PhD in
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. Design and evaluation of ephemeral, user-configurable, and composable data and storage systems. Design system-level approaches for time-sensitive or data-intensive processing of data originating