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Field
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, demonstrated by a strong publication record: 1) bioinformatics and related areas; 2) cell and molecular biology and related areas; or 3) animal model physiology and related areas. Candidates must have a PhD, or
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sequencing, Hi-C, and other protocols bioinformatic and statistical analysis of complex datasets that include numerous types of data including 16S, metagenomic, metatranscriptomic, and enriched metagenomic
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, Agricultural and Biological Engineering 80% Performing research (protein characterization, bioinformatics) 20% Contributing to reports, manuscripts, project reporting, and grant proposals Additional Information
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, Agricultural and Biological Engineering 80% Performing research (protein characterization, bioinformatics) 20% Contributing to reports, manuscripts, project reporting, and grant proposals Additional Information
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repertoires of different viral groups groups, and the development of bioinformatic methods for genomic and evolutionary analyses. The research will address critical questions regarding the evolution and
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visit: hr.ufl.edu/benefits Required Qualifications: A PhD in any area of ecology, evolution, or related fields. Experience with genomics, transcriptomics, and bioinformatics or motivation to acquire
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cancers. The training provides epidemiology and bioinformatics fellows with the specialized skills to incorporate novel high-throughput technologies into large-scale collaborative epidemiology studies and
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Job Description The Yale School of Medicine, Department of Psychiatry, is recruiting one highly motivated and successful bioinformatics postdoctoral associate to begin this fall, who aspires
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record: 1) bioinformatics and related areas; 2) cell and molecular biology and related areas; or 3) animal model physiology and related areas. Candidates must have a PhD, or MD/PhD degree, and be self
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-transmission electron microscopy. -Develop bioinformatics workflows for processing and analyze large data sets. -Perform key laboratory techniques such as PCR, molecular cloning, SDS-PAGE, and other basic