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Field
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Biostatistics & Bioinformatics Duke University invites applications for a postdoctoral associate in scientific machine learning (SciML) as part of a new NIH-funded Center for Excellence in Multiscale Immune
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of the relevant fields (e.g. Plant Pathology, Mycology, Microbiology, Population genetics, Genomics, Bioinformatics or related science). Preferred Qualifications: Strong background in fungal biology & genetics
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, imaging techniques and bioinformatic analysis of microscopy images, RNAseq data and/or spatial transcriptomics. Experience with confocal imaging, human fetal cortex tissue, RNAseq and image analysis are all
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. cerevisiae yeast . Expertise in omics methods. . Preferred: ability to perform bioinformatic analyses Interpersonal skills. Independence. Ability to work in a team and adapt to the needs of colleagues
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organizational skills. Proficient user of Microsoft Office Suite. Skills and ability to perform bioinformatic analysis of transcriptomic data. Skills and ability to perform metabolic analysis (e.g. Seahorse
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microbial ecology, with experience in high-throughput sequencing techniques and bioinformatics analysis. Expertise in soil science, including soil nutrient cycling, soil microbiology, and ecosystem processes
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scheduling to accommodate time-sensitive experimental procedures. Who we are looking for A dedicated researcher with a PhD in neuroscience, cell biology, molecular biology, bioinformatics, or a related field
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either four of these bioinformatics tools: BLAST, Ensembl, InterProScan, Primer3, MEGA, MAFFT, Phytozome, Bioconductor, Geneious, Clustal Omega Proficiency in R Knowledge of plant stress biology Good
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immune responses. Highly motivated candidates with recently obtained Ph.D.s or equivalent degrees in immunology, molecular biology, cell or developmental biology, or bioinformatics are invited to apply
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 16 days ago
/Description: The Postdoctoral Research Associate will independently conduct biomedical research on substance use disorders using molecular/omics, behavioral, and computational/bioinformatic techniques, analyze