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happens, and how it can be made better. This is a role for someone who’s excited to work with big, messy, real-world data — and who wants to do more than just build models. We’re looking for a researcher
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: Experience combining large clinical and research data sets. Interested and comfortable working with pediatric patients with special needs. A track record of publications in relevant fields. Required
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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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, submit the required application materials, or find out more information, please contact Dr. Brian Kim (kimjb at stanford edu). The position will remain open until filled. Does this position pay above the
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disciplines and mentors Stanford Departments and Centers: Med: Biomedical Informatics Research (BMIR) Biomedical Data Sciences Postdoc Appointment Term: 1 year minimum with the option to extend. $75,000+ per
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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
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on hotspot detection. This modeling work is well supported by large-scale primary datasets, including survey-based, parasitological, serologic, and genomic data. Relevant methodologies include mechanistic
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Materials: Please send your application package as a zipped file to kseetah@stanford.edu (link sends e-mail) , with the subject line: Application for 'Integrating Natural and Cultural Data' postdoc. Does
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and analysis. Experience managing large datasets and executing data analysis in complex environments is highly valued. Required Application Materials: Application Instructions To apply, include
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healthcare innovation, leveraging big data to improve patient care and outcomes. The successful candidate will focus on designing, training, and implementing novel deep learning models, particularly large