95 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions at University of Washington
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of transcripts and/ or proof of academic good standing (transcript of highest degree conferred; proof of academic good standing on official letterhead and signed by graduate program director, advisor
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for postdoctoral researchers is provided through the Office of Postdoctoral Affairs, Career Center, Teaching Center, and campus groups. Applicants should be recent PhD graduates in Neuroscience or related fields
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will contribute to our overall goal of advancing novel therapeutic targets for neurodegenerative disease. Candidates with backgrounds in computational biology, stem cell biology, or neuroscience
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associated clinical outcomes. The fellow will be responsible for identifying computational approaches for data selection, processing, and predictions/inference. The expected outcome of the project is to
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unique interdisciplinary environment where world-class researchers with expertise in computing and software, biochemistry, genome sciences, biological structure, pharmacology, immunology and other basic
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Interaction Position Details Position Description Postdoctoral Scholar in the Department of Speech and Hearing Sciences and Institute for Learning & Brain Sciences University of Washington: Academic Personnel
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microbiome data and/or analyzing sequencing data in a high-performance computing environment. Experience in BSL2 laboratory and familiarity with ELISA techniques. Demonstrated fieldwork experience in community
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University Personnel to learn how your demographic data are protected, when the data may be used, and your rights. Disability Services To request disability accommodation in the application process, contact
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unique interdisciplinary environment where world-class researchers with expertise in computing and software, biochemistry, genome sciences, biological structure, pharmacology, immunology and other basic
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level. The position requires working collaboratively with a team of experimental and computational biologists to integrate genetic and genomic data with mathematical modeling to better understand