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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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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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to) the qualifications of the selected candidate, budget availability, and internal equity. Pay Range: $86,100 Aligning Machine Learning Models with Algorithmic Reasoning Tasks We are seeking a postdoctoral researcher to
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chain network analysis and geospatial modeling. The successful candidate will have strong data science skills, including experience working with large, complex data from varied sources, and machine
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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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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 scientific
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environment provides many professional growth opportunities in academia, entrepreneurship, and public service. Responsibilities include: Investigate cutting-edge techniques in system modeling, analysis, and
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language processing (NLP) to augment clinical decision-making and expand access to high-quality healthcare. Our lab develops new methods to improve model trustworthiness and leverages heterogeneous clinical data