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these methods as an important addition to the Biomedical Informatics’ body-of-knowledge, with the purpose of improving clinical applications and enhancing medical care. Required Qualifications: A PhD in
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particular, the postdoc will focus on applying reinforcement learning to discover vulnerabilities and failure modes in software systems that support critical infrastructure, in particular AI-based decision
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with a strong background in cognitive or computational neuroscience, with an emphasis on neuroimaging techniques and computational methods. The ideal candidate will possess not only a deep conceptual
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experience to address issues of equity in applied early childhood settings a PhD or EdD in education, developmental psychology, economics, sociology, or a related field within two years of the date
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of the selected candidate, budget availability, and internal equity. Pay Range: $80,000-95,000 The Alsentzer Lab at Stanford is seeking a postdoctoral fellow to advance trustworthy, deployable AI methods
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education research arcs, outstanding teachers, and careers in surgical education. The fellowship consists of extensive opportunities in education research, formal training in grant writing, medical education
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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
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systems. Includes establishing medical reasoning benchmarks and automated / scalable evaluation methods. Developing recommender algorithms to predict specialty care with large-language model based user
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. The position is fully funded. Required Qualifications: The successful candidate should be highly motivated and hard working, with outstanding past research success and publication history, with an MD, PhD or MD
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excellent benefits and competitive salaries. Support is available for 1-year appointment with renewal up to 3 years of training and includes: Tuition, books, and software; Research-related costs; Conference