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-of-the-art sparse algorithm in matrices, tensor and networks for large-scale numerical, scientific and AI models and disseminating findings through publications and presentations in top-tier peer-reviewed
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the U.S. DOE Weatherization Assistant Program and the weatherization network by developing tools and resources for building energy audit and health and safety assessment; providing training and assistance
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utilization across the computing continuum. Additionally, you will investigate innovative approaches to optimize the balance between performance and resilience, considering the complexities of heterogeneous
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to enable quantum computers, devices, and networked systems. It develops community applications, data assets, and technologies and provides assurance to build knowledge and impact in novel, crosscut-science
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on ab initio data to accurately model the thermodynamic and thermophysical properties of complex materials. Conduct molecular simulations to elucidate the thermodynamic and structural basis of enhanced
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necessary for simulating and understanding complex, multi-scale systems. The group is part of the Mathematics in Computation (MiC) Section of the Computer Science and Mathematics (CSM) Division. CSM delivers
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. Understanding of machine learning algorithms (gradient descent, random forests, etc.) and deep neural network architectures (ResNet and Transformers). A broad understanding of machine learning methodologies and
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macromoleculartechniques and analysis is required. Experience in protein expression and purification in prokaryotic systems. Experience in crystallization, structure determination and analysis of protein-ligand complexes
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(https://cbi.ornl.gov/ ). The Plant Systems Biology Group seeks to explore and understand the network of traits, genes, proteins, metabolites, and environmental signals that lead to improved plant
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, or similarly complex, thermal energy systems. Experience with commercial CFD codes such as STAR-CCM+, ANSYS Workbench or COMSOL Multiphysics, open-source CFD codes such as OpenFOAM or Nek5000, optimization and