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, project reviews, and public-facing events. Contribute to research proposals, intellectual-property development, and future scale-up activities. Required Qualifications: PhD in mechanical engineering
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of computational methods into clinically interpretable tools for bedside monitoring. Required Qualifications: PhD, MD, MD-PhD, or equivalent degree in biomedical engineering, electrical engineering, computer
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Qualifications: A PhD, MD/PhD, or equivalent research doctoral degree in neuroscience, biomedical data science, computer science, psychology, psychiatry, statistics, engineering, applied mathematics, or a related
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an impact on human health and the environment. The mission of the new Electrification for Health program is to improve health through clean electric systems that reduce air pollution indoors and outdoors and
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for recent MD and PhD graduates who are passionate about leveraging computational methods to transform trauma and acute care surgery. Fellows will work at the intersection of clinical medicine, data
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. Current and emerging areas of work include: Life-course and translational aging research, including integration of aging science across the Stanford Clinical and Translational Science Award (CTSA) program
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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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QUALIFICATIONS: PhD in computer science, electrical/biomedical engineering, statistics, applied mathematics, or a related field. Strong track record in machine learning/deep learning with imaging data