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independent strategies (metagenomics, bioinformatics, synthetic biology) to determine microbial function from sequence data. Since this project is highly interdisciplinary, we are seeking applicants from
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experience in microbiology, mass spectrometry based proteomics, metabolomics and lipidomics, NMR based metabolomics, and/or bioinformatics. key words Microbiome; Lipidomics; Bioinformatics; Proteomics; Mass
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. This project seeks to provide metaproteomic data related to standardized materials, benchmark bioinformatics workflows of standardized data, and facilitate, and/or participate in inter-laboratory/inter
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biology, mammalian cell culture, digital PCR, bioinformatics, or next-generation sequencing library preparation and analysis are encouraged to apply. References: Development and Characterization
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, Bioinformatics; Microbial mixtures;
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bioanalytical chemistry, and bioinformatic data analysis. We invite applicants from diverse backgrounds, and successful applicants should expect to collaborate closely across an interdisciplinary team. Microbiome
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development, microfabricated device design and development, measurement of samples with ultrahigh throughput sequencing and microarrays, and bioinformatic/biostatistical data analysis of the large data sets
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Biotechnology 2019, 37, 561. [2] P Krusche, et al, JM Zook. Best practices for benchmarking germline small-variant calls in human genomes. Nature Biotechnology 2019, 37, 555. key words Genomics; Bioinformatics
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practices for benchmarking germline small-variant calls in human genomes. Nature Biotechnology 2019, 37, 555. Genomics; Bioinformatics; DNA sequencing; De novo assembly; Machine learning; Reference materials
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. Nature Biotechnology 2019, 37, 555. Genomics; Epigenetics; Transcriptomics; DNA methylation; Bioinformatics; Sequencing; Machine learning; Reference materials; Precision medicine; Data science; Artificial