12 complex-network Postdoctoral research jobs at Oak Ridge National Laboratory in United States
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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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processing software Knowledge of in situ neutron and x-ray scattering/tomography techniques for materials examination Experience with complex mechanical testing of materials Flexibility to adapt evolving
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environment. You will play an integral role in the development of PiFM and closely collaborate with other scientists across the network of NSRCs for synthesis, device fabrication, theoretical calculations, and
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, as necessary. Support research and development on alternative target designs, including alternative material matrices for pressed cermet pellets, complex geometries of pellets, novel encapsulation
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to achieve equitable, reliable and adaptable built environments through data ecosystems creation, data science and integrated complex systems analysis. The group’s vision is to enable a sustainable, safe, and
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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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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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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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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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. 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