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model fairness and model generalizability across multi-institutional electronic health records databases. The researcher will have access to the real-world EHR data from almost 20 sites across
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expected to continue the Lab’s ongoing research projects in one or more of the following areas: Glaucoma Neuroimaging and Neuroprotection in Humans and Experimental Animal Models; The Neural Basis of Sensory
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biology, glycoprotein science, protein mass spectrometry and animal models would be valuable but is not essential. Required Application Materials: CV or biosketch Names of 3 references Stanford is an equal
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position will require establishing new model species in the lab, developing protocols for experiments that have not been attempted before, and collaborating with an international and interdisciplinary team
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of the post-doc is to study how innovations in AI, especially adaptation of Large Language Models (LLMs) architectures for time-series data, can be used in study of aging, health span, and longevity
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scholars to join our research team. Specializing in infectious disease epidemiology and public health modeling, we study vaccine-preventable infections (e.g., SARS-CoV-2, pertussis) and neglected tropical
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working with large healthcare datasets (EHRs, claims, registries). Proficiency in R or Python. Strong quantitative skills and familiarity with advanced modeling techniques. Excellent written and verbal
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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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spectrometry and animal models would be valuable but is not essential. Required Application Materials: Candidates should submit their CV. They will be asked for 3 individuals who can serve as a reference
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expertise in Large Language Models (LLMs), Agentic Systems, as well as strong interdisciplinary teamwork skills and communication skills. About the Stanford NLP Group: Stanford NLP Group focuses on basic