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time of appointment. Demonstrated expertise in bioinformatics, statistics, microbiome data analysis, and/or computational methods. Experience working with large population-level datasets (e.g., NHANES
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Analysis of food ingredients, especially HPLC, IC and CE methods and photometric assays Good communication skills and high motivation to engage students and the general public Experience in teaching of
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: 18555785); Nature Immunology (PMID: 31086333): Nature Cell Biology (PMID: 30778220). The Postdoctoral Fellow will conduct experiments, perform data analysis and prepare manuscripts in addition to attending
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, transcriptome analysis and gene regulation is highly desirable. 3). Solid publication record. The fellow will work closely with the Pl and others on the research team. We support the career progression
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disease. Key responsibilities Lead and conduct the processing and statistical analysis of large-scale long-read RNA and DNA sequencing, single nuclei RNA sequencing and spatial transcriptomics
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increasing independence over time. Collaborate on project and analysis design guided by their PI. Develop new computational methods. Adhere to field and lab standards for data analysis. Identify, process
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, light sheet, two-photon microscopy), multi-omics (single cell/spatial transcriptomics/proteomics, phospho-proteomics, ATACseq, metabolomics), and whole organoid level analysis (morphometry, Ca2
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of the following methodologies: optogenetics, calcium imaging, viral tracing, tissue clearing, murine behavioral phenotyping, machine-learning behavioral analysis Familiarity with programming languages
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cells and mice) and willingness to work with animal models and patient samples - Experience in handling omics data, programming and analysis software. Experience in biostatistics/data science are
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GWAS and post-GWAS analysis; and comfort with bioinformatics. This is highly collaborative work, so the candidate should also be able to work cooperatively with peers at Yale and with many other