347 distributed-algorithm-"Meta"-"Meta"-"Meta" Postdoctoral positions in United States
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distributed quantum computing. The center includes other quantum faculty, and conducts a wide range of collaborative quantum research in the areas of quantum computing, quantum algorithms and complexity
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Group , a leader in innovative multi-sensor atmospheric remote sensing from ground, airborne, and satellite platforms. Our group develops advanced algorithms and data analysis methods to address
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Requisition Id 15472 Overview: We are seeking a Postdoctoral Research Associate who will contribute to the development and implementation of novel tensor network algorithms and their combination
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Group , a leader in innovative multi-sensor atmospheric remote sensing from ground, airborne, and satellite platforms. Our group develops advanced algorithms and data analysis methods to address
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. The participant may also have the opportunity to be involved with the development of novel algorithms, bioinformatic tools or analytical pipelines that quantify the diversity of RNA viruses that may be deployed in
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implements machine and deep learning programs. Develops algorithms to deconvolve RNA-seq data and compare them to AI-based methods. Performs follow up validation efforts on cell lines. Minimum Qualifications
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verification algorithms and prototypes on large microgrids, Naval systems, and utility systems. ● Assist grant proposal writing, work collaboratively with industry and government, and mentor graduate
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maintaining the DataSpaces (https://dataspaces.sci.utah.edu/download/ ) project – a high-performance distributed data management framework designed for in-memory data staging and coordination in scientific
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Duties/Tasks: Research and Development Formulate and analyze models for transmission/distribution, microgrids, and shipboard power systems (steady-state and dynamic). Design optimization and control
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), to work on problems at the intersection of biology, medicine, mathematics and computation. The successful candidate will contribute to the development of next-generation learning algorithms to understand