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is to integrate computational modeling with experimental methods and provide innovative solutions for technology growth. We aspire to help generate technical artifacts (patents) as well as scientific
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Qualifications: Ph.D. (within 0–5 years) in computational bioscience, computational biophysics, computer science, or a related field Strong programming skills in C++, Python, or similar scientific computing
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performance modeling, static analysis, or PIM/heterogeneous architecture research. Knowledge of large-scale scientific computing applications and algorithms (sparse linear system solvers, dense matrix
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simulation software related to radiation transport and computational fluid dynamics. Conduct performance profiling of existing scientific software to identify bottlenecks and implement strategies for improving
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Requisition Id 16198 Overview: Oak Ridge National Laboratory is the largest US Department of Energy science and energy laboratory, conducting basic and applied research to deliver transformative
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science, and materials engineering, with emphasis on understanding material behavior in complex chemical and radiological environments. Research activities may include the design of functional nanomaterials
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management, workflow management, High Performance Computing (HPC), machine learning and Artificial Intelligence to enhance our capabilities in making AI-ready scientific data. As a postdoctoral fellow at ORNL
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), including data analysis and some modeling. Work with others to maintain a high level of scientific productivity; the job holder will interact regularly with senior scientists, program managers, and group
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array of capabilities in nuclear nonproliferation, data analytics, cybersecurity, cyber-physical resiliency, geospatial science, and high-performance computing, our organization seeks to produce world
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research at the intersection of quantum information science and fundamental materials science focused on understanding the coherent dynamics of optically accessible spins in bulk and van der Waals materials