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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
. Techniques would include the use of CRISPR/Cas9-targeted gene deletion, microbead and FACS cell purification, flow cytometry analysis, Western blot, qrt-PCR, ELISA, RNAseq, scRNAseq, micro-CT imaging, IHC
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–biodiversity relationships are linked to acoustic comfort–restoration outcomes. The models will integrate spatially-explicit structural complexity variables, landscape imperviousness variables, biodiversity
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cutting-edge multi-omics at bulk, single-cell and spatial scales with computational analyses to investigate transcriptome, epigenome and chromatin architecture. Combine multi-omics with flow cytometry and
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disease, and identify causal genes and variants using xQTL analysis and integrating our data sets from hundreds of brains (sn-RNAseq, sn-ATAC-seq, sn-long-read PacBio RNAseq, high-resolution spatial
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management systems, i.e., MySQL or Microsoft SQL Server. · Proficient in traffic simulation and spatial analysis. · Experience writing and publishing manuscript(s) that report original research
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or TransCAD) or open-source transportation modeling software (i.e., MATSim and DTALite); Advanced knowledge of spatial analysis, econometrics, and/or machine learning. Additional Certifications: Additional
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ecologist (m/f/d) with a background in community ecology, macroecology, metacommunities, and/or analysis of ecological time series. The applicant should have a strong track record of scientific publications
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analyse complex data from emerging genomic pathology approaches, including CRISPR, single cell sequencing, spatial transcriptomics, and image analysis to address biologically- and clinically-driven