87 algorithm-development "https:" "Simons Foundation" Postdoctoral research jobs at Stanford University
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will be focused primarily on the development and application of novel computational algorithms to analyze and integrate diverse omics datasets, including single-cell RNA-seq, spatial transcriptomics and
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disease progression. This includes integrating LLMs with structured data sources to develop robust computational phenotyping algorithms and scalable models for real-world evidence generation. The role will
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developments in sensor design, dataset transmission, data analysis, and numerical modeling to distinguish between normal and abnormal features. Here, the goal is to develop machine learning algorithms
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University. This research opportunity will be focused primarily on the development and application of novel computational algorithms to analyze and integrate diverse omics datasets, including bulk and single
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funded by the Simons Foundation that aims to uncover how opportunities for action ("affordances") shape neural representations, perception, and behavior. Why this position? You will sit at the center of a
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typologically diverse languages Creating self-supervised learning algorithms that can assess phonological development and speech complexity in children from birth through age 6, with applications to both typical
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research. The ideal fellow will be interested in developing and applying novel computational algorithms to novel datasets generated in the setting of non-neoplastic and neoplastic disease. Key
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Stanford Cancer Center Pediatrics Postdoc Appointment Term: Two years Appointment Start Date: 1/1/2026 Group or Departmental Website: http://www.sheltzerlab.org (link is external) How to Submit Application
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Appointment Term: 1-2 years depending on performance and availability of funding Appointment Start Date: Summer/ as soon as possible Group or Departmental Website: https://sparklab.stanford.edu/ (link is
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Affairs. The FY25 minimum is $76,383. The research group led by Dr. Zihuai He (https://profiles.stanford.edu/zihuai-he (link is external) ; https://www.zihuai-he.com/ (link is external) ) at Stanford