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. The postdoc will be expected to take intellectual ownership of a research program, lead scientific manuscripts, present findings at national and international meetings, and collaborate with clinical and
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Expertise in machine learning, including building and deploying prediction models Strong data science coding skills in programs and languages such as Python, R, Stata, and SQL Experience with research in
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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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. Preferred Qualifications: Experience with large language models, natural language processing, transformer-based models, retrieval-augmented generation, or LLM application programming interfaces. Proficiency
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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
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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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(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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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