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NRC Research and Fellowship Programs Fellowships Office Policy and Global Affairs Sign In Home Sign In sign in | focus There was an error in opening this page. If the error continues to occur, please write to fellowshipsoffice@nas.edu for support. Copyright © 2024. National Academy of Sciences....
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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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processes of the organism at a given time and enables a characterization of the range of health parameters one would expect in changing environments. By probing the health status of a myriad of species, we
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NIST only participates in the February and August reviews. In situ characterization of advanced ceramic sintering processes The past decade has seen the development of several novel methods
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Description Electromagnetic techniques can provide a means for rapidly analyzing or processing biochemical samples in a manner that can be readily scaled up to handle large numbers of samples in massively
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less). To address this technological bottleneck, we are developing a new technology platform--next gen protein sequencing--based on large-scale, massively parallel, single-molecule peptide sequencing
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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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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