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-cell RNA-seq, ADT-seq, ATAC-seq, DNA-seq, and spatial transcriptomics in the study of human hematopoiesis and myeloid malignancies. The scholar will aim to identify biomolecular features of aging
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Postdoctoral Affairs. The FY27 minimum is $79, 056. We are generating spatial transcriptomic/multi-omic data on neoplastic and non-neoplastic diseases. We are hoping to recruit a postdoctoral fellow to lead the
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Description Join a pioneering project at Stanford University to create “A Spatial Transcriptomic Atlas of Embryo-Endometrial Crosstalk During Implantation and Human Embryo Development”. This position is funded
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for all postdoctoral scholars appointed through the Office of Postdoctoral Affairs. The FY27 minimum is $79, 056. We are seeking a postdoctoral fellow to work on cutting-edge single-cell and spatial-omics
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quantitative survey datasets using R (preferred) and Stata or other packages as necessary. Analyze data to assess prevalence of lead exposure sources, associations with key outcomes, and spatial trends. Support
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will be focused primarily on the development and application of novel computational algorithms to analyze and integrate diverse omics datasets, including single-cell RNA-seq, spatial transcriptomics and
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spatial and temporal monitoring results in enormous volumes of data, necessitating the management of large datasets and communication of extensive (and expensive) data packets. These factors necessitate new
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. The successful candidate will have strong data skills, including experience handling complex data structures, working with spatial data, and causal approaches. The goal of this position is to provide advanced
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are an interdisciplinary research team that integrates single-cell and spatial genomics, lineage tracing, synaptic proteomics, functional perturbation screening, and machine learning to investigate how the human brain
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for Spatial Biology Description: The Lu Lab at Stanford University is seeking a postdoctoral fellow with deep expertise in advanced AI and generative modeling to develop computational frameworks that transform