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Field
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models to evaluate therapeutic efficacy and pharmacokinetic profiles. Gaining exposure to cutting-edge transcriptomic, proteomic, and "imageomic" (high-content image informatics) datasets, as
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, multidisciplinary collaborative research environment. Primary Responsibilities Lead the state-of-the-art research using genetic mouse models for histology, single-cell transcriptomic, and spatial transcriptomic
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execute bacterial perturbation experiments, develop scalable molecular biology workflows, and generate high-quality transcriptomic, physiological, proteomic, and metabolomic datasets. This position offers
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, biostatistics, computer science, biomedical informatics, genomics, systems biology, quantitative biology, or a related field. Demonstrated experience analyzing genomic, transcriptomic, or other high-dimensional
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Identification of protective malaria antigens Regulatory T-cell and inflammatory responses during infection Systems immunology and high-dimensional immune profiling Single-cell transcriptomics and T-cell receptor
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. Utilize digital pathology, computational pathology, genomic, and transcriptomic approaches to analyze tissue cohorts for translational biomarker discovery projects. Contribute to tissue biobanking and
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-generation sequencing and single-cell technologies (e.g., scRNA-seq, scATAC-seq, scTR-seq, and/or spatial transcriptomics). Previous experience in both Bioinformatics/Genomics and Cancer Biology is desirable
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cancer models Experience with single-cell/single-nucleus genomics and spatial transcriptomics Computational analysis skills in R and/or Python A record of first-author publication To apply: Please send a
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, scATAC-seq, scTR-seq, and/or spatial transcriptomics). Previous experience in both Bioinformatics/Genomics and Cancer Biology is desirable. The Postdoc is expected to collaborate closely with experimental
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: Exempt Work Schedule: Monday – Friday, 8 a.m. – 5 p.m. Summary Baylor College of Medicine is seeking a highly motivated Postdoctoral Research Associate for an integrative analysis of transcriptomic