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for analysis of epidemiological data and large scale ‘omics data such as epigenomics, transcriptomics, miRNA, metabolomics, epigenetic aging. Analyzes data and writes interpretative reports. Verifies
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include, but are not limited to, (i) the study of cancer immunology using genetically engineered mouse models, (ii) molecular analysis of epigenetic crosstalk, and (iii) the effects of these epigenetic
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function. Knowledge and/or experience in high dimensional and conventional flow cytometry. Mouse handling and tissue processing. Generation and analysis of bulk and/or single cell transcriptomic data
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component of the UW School of Medicine and shares UW Medicine’s mission to ‘Improve the Health of the Public.’ We accomplish this by providing the best care we can today, conducting research to develop better
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unless stated elsewhere in the job posting. Work Experience: No additional work experience unless stated elsewhere in the job posting. Skills: Collaboration, Data Analysis, Data Interpretations
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additional work experience unless stated elsewhere in the job posting. Skills: Bioinformatics, Biomarkers, Computer Science, Data Analysis, Etiology, Exome Sequencing, GATK, Genetic Research, Linux
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unless stated elsewhere in the job posting. Skills: Collaboration, Data Analysis, Data Interpretations, Experimentation, High Performance Computing (HPC), Laboratory Operations, Laboratory Techniques
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platforms, Docker). · Experience with GIS/spatial analysis and traffic simulation or microsimulation tools. · Evidence of scholarly productivity (peer-reviewed manuscripts) and experience
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by a U.S. Department of Labor prevailing wage determination. depending on experience. Job responsibilities 1. Research Duties (90%) a. Develop analysis protocol for video-audio recordings
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profiling (PhIP-Seq), from library preparation to data analysis. · Perform a range of molecular biology assays (RT-qPCR, ddPCR, sequencing, etc.) and troubleshoot as needed. · Analyze and