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Learning in Everyday Environments Advisors: Monica Ellwood Lowe, Ph.D., Meg Cychosz, Ph.D., Dan Jurafsky, Ph.D. We are recruiting a postdoctoral scholar to join a collaborative, interdisciplinary team
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collection settings (preschools, homes) using a variety of methods (child-centered wearables, deep learning, fNIRS, eyetracking). The postdoc will primarily be mentored by Meg Cychosz (Linguistics), but
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, and collaborative Postdoctoral Fellow to join our team and conduct research focused on physiologic waveform analysis, biomedical signal processing, and computational modeling of continuous clinical
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therapeutic targets using large-scale human datasets, including cardiovascular imaging, genetics, omics, EHR data, and clinical outcomes. Ongoing work builds on deep-learning phenotypes from
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contribute to grants, workshops, and collaborative project development. Environment The fellow will join a highly collaborative research ecosystem spanning the Stanford Translational AI (STAI) Lab
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-backed assessments to advance learning, accelerate research on learning differences, and foster equitable access to high-quality, data-driven decision-making for all. ROAR is now approved as a universal
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lab provides training, close mentorship, and a collaborative environment for learning across disciplines. What we do The Sun Lab brings together single-cell and spatial genomics, circuit neuroscience
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external) How to Submit Application Materials: If you are passionate about reproductive biology and want to work in a highly collaborative and innovative environment, we encourage you to apply. To
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cardiac surgery outcomes research and predictive analytics using advanced statistical and machine learning methods applied to large claims and electronic health record databases and multimodal data
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work in a highly collaborative, inclusive and supportive environment including other scientists, physicians, residents, and students. This position is NIH-funded and the researcher will work closely