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transdisciplinary network. Required Qualifications: A completed Ph.D. in a relevant field, such as the social sciences, environmental studies, sustainability science, science and technology studies, public policy
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engineering, and advanced analytics to develop novel approaches that improve patient outcomes and expand access to life-saving surgical interventions. The fellowship includes opportunities for mentorship
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: Ph.D. in Linguistics, Cognitive Science, Psychology, Electrical Engineering, Computer Science, Education, Speech & Hearing Sciences, or a related field. Substantial experience with at least one of the
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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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to intervention). Researchers face these same challenges creating a bottle-neck to research at scale. While education technology companies have built products that lower the demands on teachers, many
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endoplasmic reticulum (ER) membrane. The project will combine cutting-edge approaches in functional genomics, mechanistic cell biology, cryo-electron microscopy, and protein engineering. We are particularly
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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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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