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; Microbial Communities; Flow Cytometry; Microbiome; Reference Materials; Bioinformatics; Engineering Biology;
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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
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electrophoresis; DNA; Forensics; Genotyping; Multiplex PCR; Real-time PCR; Short tandem repeat; Single nucleotide polymorphism; Digital PCR; Next generation sequencing; DNA mixtures; Bioinformatics; Eligibility
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Multiscale modeling of complex electrostatic processes in heterogeneous molecular environments NIST only participates in the February and August reviews. Molecular ionization, ion pairing, transport
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-and-quality-control-materials-metqual-program key words Metabolites; Metabolic pathways; Mass spectrometry; Bioinformatics; Chemometrics; Multivariate statistics; Human health; Precision medicine
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metabolomics analysis pipelines. key words metabolomics; mass spectrometry; neural networks; algorithms; machine learning; cheminformatics; biostatistics; bioinformatics; big data Eligibility citizenship Open to
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for this project include state-of-the-art automation for microbial engineering, culture, and measurement. key words Machine Learning; Biology; Bioinformatics; Data Mining; Genetics; Active Learning Eligibility
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digital models through an additive process. AM enables the rapid production of complex parts with minimal lead time, fewer constraints, and reduced assembly requirements. This makes it an attractive option
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Semiconductor manufacturing is a complex procedure with challenging variations in machines and processes. For example, due to high-mix semiconductor manufacturing, in which hundreds of types of products
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the melting point and mechanical deformation due to powder densification and compliance to a (cold) build plate. These processes give rise to material microstructures quite unlike wrought materials and that