28 multiple-sequence-alignment research jobs at Stony Brook University in United States
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genomics, spatial metabolomics, single-cell sequencing, Optical/Photoacoustic imaging, seahorse, WB, RT-PCT, immunostaining and data analysis related to these assays. The experiments also include using cell
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genomics, spatial metabolomics, single-cell sequencing, Optical/Photoacoustic imaging, seahorse, WB, RT-PCT, immunostaining and data analysis related to these assays. The experiments also include using cell
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mathematical analysis, and implementation level where actual systems for these proofs are developed for deployment in larger real world applications. An ideal candidate would have multiple publications
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culture, kidney organoid, and mouse models. Successful applicants may select from multiple projects and should have experience in most of the following areas: * Conducting experiments using cell culture and
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culture, kidney organoid, and mouse models. Successful applicants may select from multiple projects and should have experience in most of the following areas: ● Conducting experiments using cell culture
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culture, kidney organoid, and mouse models. Successful applicants may select from multiple projects and should have experience in most of the following areas: ● Conducting experiments using cell culture
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laboratories The candidate will also have immediate access to brain PET data acquired from multiple universities, including Stony Brook. This includes large (>30 participants) datasets examining
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, including integration across multiple cohorts, devising workflows and strategies to plan genetic association studies. * Conducting bioinformatics and statistical analyses of high-throughput omics data
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proteomic datasets, including integration across multiple cohorts, devising workflows and strategies to plan genetic association studies. ● Conducting bioinformatics and statistical analyses of high
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laboratories The candidate will also have immediate access to brain PET data acquired from multiple universities, including Stony Brook. This includes large (>30 participants) datasets examining