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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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Requisition Id 16262 Overview: We are seeking a postdoctoral researcher to work at the intersection of tensor networks, quantum algorithms, scientific computing, topological physics, and quantum
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environment. The successful candidate will develop and apply advanced machine learning techniques—including multimodal AI, computer vision, and large language models—to complex scientific and engineering
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, work together, and measure success. Basic Qualifications: A PhD in Materials Science & Engineering, Computational Sciences, Physics, or a related field completed within the last 5 years Demonstrated
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reside in the Materials Joining Group in the Materials Analysis and Interface Science Section, Materials Science and Technology Division, Physical Sciences Directorate, at Oak Ridge National Laboratory
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, as well as conduct their characterization. The project is highly collaborative, and the postdoc will work with other polymer scientists, physicists, computational scientists, as well as neutron
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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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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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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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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