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health more generally. Data sources for our work in this area are large-scale electronic health record data, medical claims data, mortality registries, and epidemiological cohort studies. The researcher
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, leveraging SLAC's unique strengths in photon science, advanced characterization, data/AI-enabled discovery, and cross-directorate partnerships (including strong connections to Stanford and the broader national
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computational analysis of large-scale pharmacogenomic datasets. The lab maintains active collaborations with medicinal chemists, structural biologists, and clinical oncologists at Stanford and elsewhere
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candidate will gain expertise in CRISPR screening, drug sensitivity profiling, target deconvolution, and the computational analysis of large-scale pharmacogenomic datasets. The lab maintains active
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associated with biological membranes, including large peripheral membrane complexes and integral membrane transporters. In parallel with mechanistic structural work, we develop targeted chemical probes
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to evaluate reliability, transportability, uncertainty, information sufficiency, and clinical usefulness. The postdoc will work with large-scale clinical data resources at Stanford and through national data
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, and Heart Failure Discovery We are seeking a postdoctoral fellow to work at the intersection of cardiovascular medicine, biomedical data science, artificial intelligence, genetics, imaging, and multi
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-cultural identity development and adolescent adjustment across diverse cultural and national contexts. The position offers an exciting opportunity to work as part of a large, collaborative, interdisciplinary
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primates or humans – Theoretical neuroscience, machine learning, or AI • Proficiency in Python, MATLAB, or equivalent data‑analysis frameworks. • A passion for big‑picture questions, open science, and
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identifying structures and processes that promote high quality healthcare. Our projects apply advanced analytical methods to large databases of primarily structured electronic health record data and EHR usage