64 computer-science-postdoctoral "https:" Postdoctoral positions at Stanford University
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Health Epidemiology and Population Health Health Policy Med: PCOR Neuroscience Institute Medicine, Biomedical Informatics Research (BMIR) Biomedical Data Science Medicine, Center for Digital Health Postdoc
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motivated and skilled postdoctoral researcher to lead projects related to PhacoTrainer—computer vision models for cataract surgical video recognition. Project themes will include validating PhacoTrainer
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Research (BMIR) Postdoc Appointment Term: One year fellowship, renewable up to 5 years Appointment Start Date: ASAP Group or Departmental Website: http://boussard-lab.stanford.edu/(link is external) How
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of innovation in pain research, education, and patient care. Our postdoctoral program has successfully transitioned fellows into independent research careers; many have achieved their own NIH K/R grants and
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. A full time computational biology postdoctoral position will become available in 5-6 months. Required Application Materials: A cover letter outlining research interests and career goals CV Address and
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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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at Stanford University is seeking an exceptional neuroscientist or cognitive scientist—at the postdoctoral level—to join the newly launched Simons Collaboration on Ecological Neuroscience (SCENE) https
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. The lab values rigorous science, creativity, collaboration, and welcomes scientists from all backgrounds. Selected publications are listed below. More information can be found at: https://med.stanford.edu
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connections between the lab, classroom, and society. Required Qualifications: Highly motivated postdoctoral researcher with extensive experience with item response theory models, computer adaptive testing, and
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Medicine are seeking to appoint a Postdoctoral Research Fellow to join a project developing and validating deep learning computer vision models to classify mosquito breeding habitat on very high-resolution