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modeling and networked biological systems. You will work at the intersection of high-performance computing (HPC), computational biophysics, and machine learning, leveraging leadership-class computing
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that will strengthen the nation’s leadership in creating solutions to help sustain the Earth’s natural resources. Our scientists conduct research, develop technology, and perform analyses to understand and
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data-model integration, leveraging the U.S. Department of Energy’s (DOE) Leadership-Class Computing Facilities to advance predictive understanding of complex environmental systems. Major Duties
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Research Associate to develop and apply computational technique for advanced manufacturing using high-performance computing resources. ORNL’s CCP conduct world-leading research and development in multi-scale
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postdoctoral research associate to advance the state of scientific AI by addressing cross-cutting challenges in data readiness for AI to enable scalable, reproducible AI workflows on leadership-class systems
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technology by helping to attract, develop, and retain the workforce of actinide scientists to meet the needs of the nation. Topic of Interest This position is supported by the Department of Energy Isotope
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composites), energy–water nexus, data centers, and water and wastewater sectors. Prepare technical reports, peer-reviewed publications, presentations, and briefings for DOE sponsors, laboratory leadership, and
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uniting national laboratories, academic institutions and industry partners, the QSC is endeavoring to advance American innovation and global leadership by enhancing the computational robustness, algorithmic
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production target materials. This involves the development of experimental plans to examine material properties such as thermal diffusivity, thermal conductivity, and thermal expansion – material properties