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large-language model applications in healthcare systems, systematically identifying ineffective clinical processes, bioinformatics analyses of population health, as well as more conventional outcomes
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chemistry biochemistry, molecular biology, anatomy and physiology Demonstrated technical ability in histochemistry, cell culture, microscopy, qPCR, biomaterials characterization, and advanced bioinformatics
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: Candidate must have a strong quantitative background, with a PhD in computational biology, bioinformatics or related field including bioengineering, computer science, statistics, or mathematics. Strong
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: Candidate must have a strong quantitative background, with a PhD in computational biology, bioinformatics, biomedical data science, biomedical engineering, computer science, electrical engineering, statistics
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. The project provides a unique opportunity to use clinically relevant animal models, transgenic mice, in vitro and ex vivo cultures, live cell and tissue imaging, single cell technologies, and bioinformatic
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or MD/PhD Strong programming skills, preferably in R and/or Python Previous expertise and/or interest in single-cell sequencing technologies, bioinformatics, spatial analyses, and generative AI is desired
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, DNA/RNA purification) is highly desired. Prior lab experience in molecular biology, cell culture, animal handling, or microscopy. Interest in neurobiology, genomics, or bioinformatics. EDUCATION
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willing to learn, CyTOF, sequencing-including NGS and RNA-Seq, and bioinformatics. The candidate must be quick to learn new techniques and be able to modify and adapt standard protocols. The candidate
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bioinformatics tools for data analysis Required Application Materials: Curriculum Vitae Stanford is an equal opportunity employer and all qualified applicants will receive consideration without regard to race
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culture, ELISA, protein purification, DNA/RNA isolation, and PCR. Experience in flow cytometry is preferred. Experience with CyTOF, single cell RNA-seq, and bioinformatics tools like for example R is