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therapies. Discovering tumor-stromal, tumor-immune, and tumor-ECM programs that drive therapeutic resistance, cancer progression, and metastasis. Developing and applying computational/AI-enabled spatial omics
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(e.g., All of Us, UK Biobank, and Million Veteran Program), traditional cohorts (e.g., Women’s Health Initiative), and local Stanford data. Lab members have access to state-of-the-art computational
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-development environment, including structured mentoring programs, workshops and training opportunities, seminar series, and annual departmental retreats. Beyond the lab, the sunny Northern California Bay Area
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collected through ongoing SCEC programs. This data will support the postdoc's work developing and deploying multimodal models to improve the iFIND tool, extending its current text-based approach. Primary
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compliance considerations (e.g., HIPAA), data usage agreements, and governance for imaging datasets. Training plan and milestones. Year 1: Establish data access streams, curate imaging cohorts, implement
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(but not limited to) the qualifications of the selected candidate, budget availability, and internal equity. Pay Range: $80,000–$95,000 Postdoc in the modeling of laboratory workflows to program self
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using in vivo Perturb-seq. This project is related to a new NIH-funded Program Project Grant aimed at identifying differences and similarities in gene function across vascular cell types and diseases, as
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individuals A trial testing an adapted version of CPT for individuals who use opioids, delivered within syringe service programs A trial testing an integrated CPT and Relapse Prevention (RP) intervention All
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Expertise in primary cell isolation and culture, FACS, confocal imaging, and mouse genetics is preferred Experience with transcriptomics and programming language suitable for computational analysis (e.g. R