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Posted on Thu, 07/16/2026 - 19:23 Important Info Faculty Sponsor First name: Mark Faculty Sponsor Last Name: Musen Stanford Departments and Centers: Medicine, Biomedical Informatics Research (BMIR
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, and data science. We are especially focused on understanding the interplay between genetics, lifestyle, environment, and clinical factors on cardiovascular disease risk. Our work incorporates biobanks
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demonstrated ability to design, train, and deploy large-scale models Expertise in at least one of computer vision, speech recognition, or multimodal learning, with experience in real-world technology deployment
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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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deep learning algorithm development, remote sensing, geospatial analysis. We welcome applicants from ecology, environmental science, climatology, geography, geophysics, computer science, or related
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campus as arts and sciences. The fellow will lead the development and validation of imaging-based models to predict patient response to cancer treatment (80%) and will manage the unit’s AI/ML core
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, and rigor. We leverage AI to make a measurable difference in people's lives. Our work focuses on the intersections between AI and Behavioral Science, Democracy, Social Services, Emotional Well-Being
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, physiology, molecular biology, or related field. Experience in electrophysiology, structural biology, or membrane protein biochemistry is desirable but not necessary. More important is a flair for independent
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on lung biology focused research. Required Qualifications: Highly motivated postdoctoral research with: Expertise in pulmonary vascular biology, immunology, cell, molecular, or developmental biology Prior
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the Basic Science and Engineering (BASE) Initiative of the Children's Heart Center at Stanford University and the Department of Genetics to work on understanding mechanisms of pulmonary arterial hypertension