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Field
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opportunities to use approaches including GWAS, Mendelian randomization, transcriptomics and multi-omics analyses alongside functional genetic studies in Drosophila. Particular areas of interest include
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, computational biology, and spatial transcriptomics to understand therapeutic response and accelerate translation from preclinical discovery to clinical application. The successful candidate will have experimental
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or phage genetics, molecular biology, vector biology, animal infection, microscopy, genomics, transcriptomics, biochemistry, or computational analysis, depending on expertise. Analyze data, maintain
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infection leaves durable epigenetic and transcriptional scars that shape long term immunity, inflammation, and lung repair. This position is ideal for scientists excited to combine single cell transcriptomics
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limited to, large language models and foundation models, single cell analysis, spatial transcriptomics, multi-omics analysis, cancer research, intelligent healthcare, and precision medicine. Required
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) - Perform single-cell and spatial multi-omics analyses at scale - Integrate genetics with longitudinal transcriptome, clinical, biosensor, trajectories - Contribute to discovery of disease mechanisms and
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atlas-scale pediatric single-cell and spatial transcriptomic datasets. We are particularly interested in developing AI- and agent-based approaches to nominate cell-surface antigen combinations
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-resolution microscopy such as STORM, and longitudinal live-cell imaging. Transcriptomic analysis, including bulk RNA sequencing or single-cell RNA sequencing. Computational analysis in R or Python
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, biomedical informatics, genomics, systems biology, quantitative biology, or a related field. Demonstrated experience analyzing genomic, transcriptomic, or other high-dimensional biological datasets
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approaches. Experience with cardiovascular physiology or cardiovascular disease models. Background in molecular biology techniques such as PCR, qPCR, Western blotting, transcriptomic analyses, or related