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Field
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, assessment of images, or assessment of memes. Preference for those with experience working with large scale data, millions of actors and messages. Successful candidates will work on at least two related agent
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exclusion criteria apply. For more information, please visit the University of Washington Labor Relations website . Required Qualifications: Completed PhD in biomedical engineering, electrical engineering
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deep expertise in computational approaches to social science, including but not limited to the collection and analysis of large amounts of data. The applicant will be intimately familiar with
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with photogrammetry, LiDAR alignment, or large-scale 3D data, and deep learning-based 3D vision and graphics • Familiarity with image annotation tools and dataset iteration workflows • Contributions
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of global aerosol emissions using large ensemble data from RAMIP and other data sources. Lead writing of peer-reviewed publications and present findings at scientific conferences. Contribute scientific
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over time. This, key skills include familiarity with data management or large multi-method data sets and excellent data-analytic skills, especially those relevant to complex, large longitudinal studies
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deploying large-scale genetic, biologic, peptide, and small molecule approaches to define domains and specific molecular mechanisms that can be exploited for therapeutic development against emerging cancer
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Postdoctoral Associate AI and MRI Required Qualifications: (as evidenced by an attached resume) Doctoral Degree (or foreign equivalent) in Electrical and Computer Engineering, Computational Science
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for projects examining questions in cardiovascular disease using extremely large data sets comprised of routinely-collected clinical data · Developing and maintaining requirements for access to Truveta Data and
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genomic analyses on large case-control cohorts to identify risk and response associations for diseases of interest. Performs integrative analyses of other molecular and omics data, such as gene expression