92 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" "U.S" "U.S" Postdoctoral positions at Stanford University
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in the U.S. There will also be extensive opportunities to learn more about and work with Census-held administrative records. The successful candidate will have strong data science skills, including
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Appointment Term: July/August 1, 2026 to June/July, 2027 (renewable) Appointment Start Date: August 1, 2026 (flexible) Group or Departmental Website: https://pedl.sites.stanford.edu/ (link is external) How
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or Departmental Website: https://earlychildhood.stanford.edu/ (link is external) How to Submit Application Materials: Please fill out the application form and submit materials at: https
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: Physics Postdoc Appointment Term: 2-years Appointment Start Date: As soon as possible Group or Departmental Website: http://aaronsharpe.science (link is external) http://ggg.stanford.edu (link is external
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: AY 2026-27 Appointment Start Date: September 1, 2026 Group or Departmental Website: https://ceas.stanford.edu/opportunities/postdoctoral-fellowship-chinese-studies (link is external) How to Submit
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to significantly extend our existing team’s capabilities for data scoring and analysis (e.g., with expertise in natural language processing, machine learning, or computational modeling). Finally, the
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join the group to develop AI and machine learning based software to assist clinical workflow and pre-clinical studies. Required Qualifications: Ph.D. in a physical science or engineering field Strong
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Metabolism Postdoc Appointment Term: 2 years Appointment Start Date: Rolling admission, applicants can apply as soon as possible. Group or Departmental Website: https://www.research.va.gov/programs/bd-step
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: The appointment will be for one year. Appointment Start Date: 01/15/2026 or once the position is filled Group or Departmental Website: https://woods.stanford.edu/ (link is external) https://fieldlab.stanford.edu
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subsea digital twin of deep-water mooring lines for floating offshore wind turbines. The digital twin will be integrated with machine learning algorithms for detection of primary entanglement due