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phenotyping. We are seeking for an enthusiastic Post Doctoral Research Assistant (PDRA) with strong experience in bioinformatic analyses to join our team and lead the analyses of bulk and single cell ‘omic
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with bioinformatics tools and analyses. • Experience with electrophysiology and proficiency in MATLAB/Python/R models of auditory and vestibular diseases. FLSA Exempt Full Time/Part Time Full Time Number
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responsibilities include bioinformatics analyses with a strong focus on single-cell RNA sequencing and next-generation single-cell barcode lineage tracing, as well as the interpretation of complex biological
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laboratories in CIBS. Additional duties as assigned. Knowledge, Skills, and Abilities: Deep understanding of data science, AI/ML, and bioinformatics applications in biomedical research. Experience working with
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approaches including targeted genetic murine models, primary cell culture and analysis, multi-omics and bioinformatics. The biological focus will be on vascular biology, immune cell function and metabolism
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are the following: Assists PI with epidemiological and complex bioinformatics data management and analysis in multi-omics microbiome research; conducts research processes and procedures in the PI laboratory. Assists
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are the following: Assists PI with epidemiological and complex bioinformatics data management and analysis in multi-omics microbiome research; conducts research processes and procedures in the PI laboratory. Assists
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-motivated postdoctoral researcher with a strong background in biology and experience in bioinformatics. Experience in multiplex proteomics and sequencing analysis and a track record of effective communication
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in the lab and is expected to foster the development of junior lab members. Qualifications Required Qualifications: The ideal candidate will have a PhD in microbiology, biochemistry, bioinformatics
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toxicology, with strong preference for proficiency in bioinformatics and programming to analyze and present results from large genomic datasets including bulk-RNA and DNA sequencing, single-cell sequencing