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combinatorial panning methods, including phage and mRNA display, to identify de novo peptides for promising biomarkers lacking a natural ligand or lead structure. We then optimize peptide ligands for affinity and
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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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Posted on Mon, 08/04/2025 - 17:10 Important Info Deprecated / Faculty Sponsor (Last, First Name): Knowles, Juliet Other Mentor(s) if Applicable: Frank Longo, MD PhD Stanford Departments and Centers
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the robustness to address national security challenges in cybersecurity. In particular, the postdoc will focus on applying reinforcement learning to discover vulnerabilities and failure modes in software systems
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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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at PESD are available at PESD Director, Frank A. Wolak’s web-site: https://fawolak.org/pages/papers (link is external) . Required Qualifications: PhD in relevant subject area Expertise in large scale
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of behavior. Required Qualifications: a PhD (must be conferred before appointment start date) research experience in a related field at least one peer reviewed scientific publication able to collaborate in
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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