1,794 parallel-and-distributed-computing-"Meta"-"Meta" positions at University of Washington
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Scheduled Hours 37.5 Position Summary This role provides direct and embedded support for an academic department/program and the journal Revista de Estudios Hispanicos (REH), while reporting
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Description Primary Duties & Responsibilities: Implements: Algorithms and computer software for analyzing omics-based data sets [high-throughput, massively parallel genomic/proteomic/clinical]; Data management
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Position Overview School / Campus / College: College of Engineering Organization: Paul G. Allen School of Computer Science & Engineering Title: Open Rank (tenure-track) Professor in the Paul G
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parallel computing techniques including working in the cloud. Preferred Qualifications Education: No additional education beyond what is stated in the Required Qualifications section. Certifications
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capacity needs, replication, and other distributed data issues Provide advice, consultation, and support to partners, Systems Managers, Senior Computing Specialists, and operations personnel of varying
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, questionnaires, diagnostic tests and other sources; performs basic evaluation and interpretation of collected data and prepares appropriate reports and documentation as necessary; prepares and distributes study
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computer software for analyzing omics-based data sets [high-throughput, massively parallel genomic/proteomic/clinical]; Data management and analysis solutions that aid in the storage, investigation and
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pulmonary vascular endothelial cells contributes to pulmonary vascular remodeling. Our current research program includes investigations into the role of hyperactive mTOR (mechanistic target of rapamycin) in
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recommendations to primary providers, nursing and dietician staff to optimize patient care. • Responsibilities include, but are not limited to direct patient care, drug distribution, research & education, and
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computing clusters. They will have experience in learning diverse data types generated by various platforms and technologies, including genomics, proteomics, imaging, and spatial transcriptomics data