Sort by
Refine Your Search
-
focus on machine learning in the Stanford Center Cancer Cell Therapy at Stanford University School of Medicine. We seek a highly creative and motivated scientist to perform cutting-edge computational
-
clinical shadowing experiences. Research topics range from machine learning, designing, and evaluating clinical decision support content to disintermediate scarce medical consultation resources, evaluating
-
external) How to Submit Application Materials: To begin the application process, please send an email using the subject line “Postdoctoral Position in Machine Learning for Advancing Mental Health” to Tina
-
include, but are not limited to, using the latest computational learning-driven approaches, including computational social science, foundation models and multimodal machine learning, to enhance
-
to learn these tools is required. Computer literacy, including the ability to work with Microsoft Office Suite and a willingness to learn new programs such as Redcap. Ability to prioritize
-
for healthcare. The Alsentzer Lab is an interdisciplinary research group in the Department of Biomedical Data Science at Stanford University. Our mission is to leverage machine learning (ML) and natural
-
it; as well as have theoretical skills including algorithm implementation/development and data visualization. Experience and interests include designing machine learning pipelines, building web
-
and machine learning based software to assist clinical workflow and pre-clinical studies. Recent software developed from the group has been adopted in the clinic and preclinic labs. The scientific
-
nano-mechanics, and machine learning as it applies to the field of computational mechanics. Candidates will be given opportunities to develop their teaching experience by designing and teaching a class
-
/machine learning, and/or expertise in microbiome/metabolome studies. The breath of the lab’s interests are wide. We have teams focused on identifying novel diagnostics/biomarkers using human samples. In