83 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" Postdoctoral research jobs at Stanford University
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Appointment Term: 2 years with options to renew Appointment Start Date: 01/01/2026 Group or Departmental Website: https://www.stanfordpmhw.com/ (link is external) How to Submit Application Materials: Please
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and Centers: Ophthalmology Postdoc Appointment Term: 1 year with renewal based upon performance Appointment Start Date: ASAP Group or Departmental Website: https://med.stanford.edu/kapilofflab.html
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. Responsibilities may include: Designing and conducting studies on the clinical impact of GLP-1 and other metabolic therapies Developing and applying computer vision and machine learning techniques to analyze
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or Departmental Website: https://stanford.edu/group/tanglab/ (link is external) How to Submit Application Materials: Please apply through the following form: https://forms.gle/1vic3xFvaBt8qsRw7 (link is external
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Appointment 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
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Intelligence (HAI), Stanford Digital Economy Lab Postdoc Appointment Term: 1-2 Years Appointment Start Date: Sept 1, 2026 Group or Departmental Website: https://digitaleconomy.stanford.edu/ (link is external
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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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Date: As soon as possible Group or Departmental Website: https://naturalcapitalproject.stanford.edu/ (link is external) How to Submit Application Materials: Send an email with your attachments
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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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, 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