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pharmacoepidemiologic methods. Experience with NLP or unsupervised learning methods. Prior publications in relevant fields. Required Application Materials: Cover letter detailing research interests and fit
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Substitution in the Blind; Ocular Structures and Physiology; MR Engineering and Methods Development for the Visual System. MRI experiments will mainly be conducted at research centers at the Stanford campus and
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methods to improve prediction model generalizability, model fairness, and generalizability of fairness across different clinical sites. The researcher will have the opportunity to use machine learning and
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The Stanford Abdominal Diffusion Group is seeking thoughtful, motivated and collaborative postdoctoral fellows to join a growing team developing motion-robust multi-shot DWI methods for liver, pancreatic, and
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implementing novel strategies for an Adult Editing System, establishing robust Cas9/gRNA delivery methods for somatic cells in adult organisms. You will collaborate closely with a dynamic, multi-disciplinary
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training and experience; Proven knowledge in field of research; Experience in a variety of research techniques/methods and follow-up data collection; Knowledge of research procedures and protocols gained
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substitution in the EGFRvIII peptide significantly increases survival in an animal model of glioblastoma by enhancing proteasomal processing. We also developed robust methods to detect a new class of non
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of application a track record of successfully completing several quantitative methods or mixed method graduate courses a dissertation or published manuscript that relies on a quantitative or mixed-method approach
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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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from real world longitudinal data on management and health outcomes for children with mental health conditions. Methods have included deep learning, large language models (LLM), generative AI models (Gen