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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
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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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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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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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industry. You will have the opportunity to interface directly with program sponsors and lead proposal development teams. Major Duties/Responsibilities: Developing advanced modeling and optimization methods
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on reliability, security, and resilience of microgrid systems. This includes advanced control system design, modeling and analysis, control architecture design and communication-based control and optimization
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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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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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Posting Details Position Information Fiscal Year 2024-2025 Position Title Postdoctoral Associate (PRODiG+ Scholar), Computer Science Classification Title Postdoctoral Associate Department
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 8 hours 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