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species. It can be fine-tuned for downstream applications such as predicting genetic perturbations, optimizing photosynthetic apparatus for performance, selecting top performing genotypes for various
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computed tomography (CT) reconstruction, including sparse-view and limited-angle algorithms, and the application of advanced machine learning (ML) and computational imaging methods to scientific and
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to work independently and to participate creatively in collaborative teams across the laboratory. Applicants cannot have received their Ph.D. more than five years prior to the date of application and must
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of high-performance computing and its applications. An excellent record of productive and creative research, as demonstrated by publications in top peer-reviewed journals. Strong problem-solving skills and
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details. Special Requirements: Applicants cannot have received their PhD more than five years prior to the date of application and must complete all degree requirements before starting their appointment
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for the manufacturing of next generation materials for different potential market applications to evaluate the life cycle economic, energy, and environmental impacts. The focus of these analyses is to understand
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to accomplish multiple tasks within deadlines, and adapt to ever changing needs Please contact Sachin Nimbalkar at nimbalkarsu@ornl.gov or (865) 576-3590 for further details. Special Requirements: Applicants
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to improve outcomes for application spaces. Experience with techniques for analysis of thermal transport properties such as laser flash diffusivity analysis, transient plane source method, dilatometry, and