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Field
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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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scientific facilities: The CFN conducts research on nanomaterial synthesis by assembly designing precise architectures with targeted functionality by organizing nanoscale components. The CFN researches and
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of the four campuses (two in Chicago, one in London, and one in Hong Kong) reflects the architectural traditions of its environs while offering a state-of-the-art learning environment. Chicago Booth is proud
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, and measure success. Basic Qualifications: PhD degree in a related scientific field (e.g. architecture, architectural/mechanical/electrical engineering) completed within the last five years. Proven
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U.S. Department of Energy (DOE) | Washington, District of Columbia | United States | about 2 months ago
or to advance professionally. Preferred Qualifications A Master's or a Doctoral degree in one of the following disciplines: Artificial Intelligence, Computer Architecture and Grids, Computer Science
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systems, urban technology, networks science, information, decision and complex networks, computational and infrastructure intelligence, revenue and finance, complex systems architectural design framework
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high-fidelity qubit control and further ingredients for a shuttling-based architecture, using devices from academic or industrial fabrication. Key activities can include: Demonstration and experimental
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Genetics to join our team. Our mission is to advance the understanding of the genetic architecture of complex human diseases and traits, enhance our ability to predict disease, target prevention efforts in
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opportunities include battery chemistry and materials studies, electrocatalyst design and synthesis, ion exchange membranes, catalyst layer architectures, operation and test of electrolyzers/fuel cells. Strong
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cutting-edge multi-omics at bulk, single-cell and spatial scales with computational analyses to investigate transcriptome, epigenome and chromatin architecture. Combine multi-omics with flow cytometry and