78 machine-learning "https:" "https:" "https:" "https:" "The Open University" Postdoctoral positions at Stanford University
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connectivity and graph-theoretic analyses Familiarity with MR sequence programming (Siemens or GE platforms) Machine learning / AI applied to neuroimaging data EEG acquisition and analysis Use of neuroanatomical
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Term: July/August 1, 2026 to June/July 31, 2027 (renewable) Appointment Start Date: August 1, 2026, with some flexibility Group or Departmental Website: https://scale.stanford.edu/ (link is external) How
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Appointment Term: 1-2 Years Appointment Start Date: Sept 1, 2026 Group or Departmental Website: https://digitaleconomy.stanford.edu/ (link is external) How to Submit Application Materials: To apply, please
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based on performance and funding). Appointment Start Date: Flexible Group or Departmental Website: https://med.stanford.edu/neurology.html (link is external) How to Submit Application Materials: Please
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/Python coding, next-generation sequencing data interpretation, large-scale data integration, and machine learning. Science: strengthen the ability to formulate hypotheses, design aims to test the
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Appointment Term: 2026-2028 Appointment Start Date: Early 2026 Group or Departmental Website: https://med.stanford.edu/bronte-stewart-lab.html (link is external) How to Submit Application Materials: Apply by
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, biologics, and cannabis. Apply statistical and machine learning approaches (e.g., sequence analysis, latent class analysis, clustering) to examine medication use trajectories and patient subgroups
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-based models as well as patient-derived xenograft models of liver cancer. This position is suitable for a highly motivated self-starter who excels in a dynamic environment offering varied learning