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laboratory (http://www.garglab.org ) uses approaches from genomics, molecular biology, systems biology, and data science to understand cellular heterogeneity. We want to understand how cell systems with
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cell immunology, mucosal immunology, and cancer immunology using animal models and single-cell multiomics/spatial transcriptomics approaches. This postdoctoral researcher will combine wet-lab molecular
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Liu Lab · Department of Cell Biology · Yale School of Medicine Title of Position Postdoctoral Associate in ER Metabolism and Organelle Biology Department and School Department of Cell Biology, Yale
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receive advanced training in: Statistical genetics and multi-omics integration Deep learning for regulatory genomics Single-cell and spatial transcriptomics Large-scale data engineering Training is highly
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: [email protected] Start date and duration: Flexible, One year Description: The Yale Department of Pediatrics is seeking a post-doctoral associate to pursue clinical research in sickle cell disease (SCD) and
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study characterizing translation functions across human 5′ UTRs (Lewis et al., Molecular Cell, 2025. PMID: 39706187). Responsibilities will include computational mining of viral metagenomic databases
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Postdoctoral Associate | Mitochondrial Genomics | Lake Lab — Yale University, Department of Genetics
individuals and cell types, and define interactions between mitochondrial and nuclear genomes. Projects will involve developing and applying new technologies to measure mtDNA variation and dynamics, performing
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Qualifications · PhD or MD/PhD in neuroscience, molecular/cell biology, bioengineering, or a related field. · Demonstrated experience in extracellular vesicle exosome biology and advanced statistical analysis
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approaches such as non-coding CRISPR screens, the Massively Parallel Reporter Assay (MPRA), saturation mutagenesis, and synthetic sequence design, alongside machine-learning models of regulatory grammar
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experimental approaches such as non-coding CRISPR screens, the Massively Parallel Reporter Assay (MPRA), saturation mutagenesis, and synthetic sequence design, alongside machine-learning models of regulatory