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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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, 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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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
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the Grammy Award-winning Buffalo Philharmonic Orchestra ; the world-class collection of modern painting and sculpture at the Albright-Knox Art Museum ; an extensive array of historic architectural treasures
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computer science knowledge. Preferred Knowledge, Skills, and Abilities: Practical experience developing novel AI/ML algorithms and models. Knowledge about hardware architectures, compilers, neural network
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collection of modern painting and sculpture at the Albright-Knox Art Museum ; an extensive array of historic architectural treasures designed by Frank Lloyd Wright, H.H. Richardson, Louis Sullivan, and Eero
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 hour ago
the ability to design and implement novel artificial intelligence algorithms. Examples of research directions could include: multimodal foundational models for biomedical data, deep-learning architectures