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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
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approaches to remove atmospheric particulate (e.g., PM2.5) pollution. The math-based subgroup focuses on the use of deep learning and generative AI to address critical problems for the electric grid and broad
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mutual agreement. Appointment Start Date: As soon as possible Group or Departmental Website: https://med.stanford.edu/solutions.html (link is external) How to Submit Application Materials: Please submit
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fellowships and NSF SBE postdoctoral awards. We especially welcome applicants with theoretical interest in child language development, strong computational and analytical skills (deep learning frameworks), and
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Stanford University required minimum for all postdoctoral scholars appointed through the Office of Postdoctoral Affairs. The FY25 minimum is $76,383. Deep Phenotyping of Learning Differences The high-level
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for Spatial Biology Description: The Lu Lab at Stanford University is seeking a postdoctoral fellow with deep expertise in advanced AI and generative modeling to develop computational frameworks that transform
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electrophysiology. We are seeking a postdoctoral researcher to lead the neuroimaging component of a longitudinal, pediatric drug trial in Neurofibromatosis type 1 (NF1). In this role, you will acquire and analyze