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appointment. See the following table for the current salary scale for this position: https://www.ucop.edu/academic-personnel-programs/_files/2025-26/represented-oct-2025-scales/t23.pdf A reasonable estimate
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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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in digital health, fitness, and rehabilitation. Preferred Qualifications Background in machine learning/deep learning is a plus. Equipment Utilized Physical Demands and Work Environment PHYSICAL
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. Target start date is January 2026. Appointment Start Date: January 2026 Group or Departmental Website: https://woods.stanford.edu/ (link is external) https://sustainability-accelerator.stanford.edu/ (link
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-of-the-art methods, datasets, and challenges Proven experience with: Video data processing for learning and inference Deep learning architectures for video analysis Python programming and PyTorch framework
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the world’s largest supercomputers (Polaris, Aurora) and some of the most advanced characterization tools in the world at Argonne and Sandia National Labs. Candidates with a background in deep learning
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practices. Attend lab meetings, seminars, and participate in departmental and university activities as appropriate. Other Duties as Assigned 5% Qualifications Core Knowledge and Abilities Deep expertise in
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/deep learning with GWAS/sequencing data and other types of omic data, as in Mendelian randomization and TWAS. In addition to new methods development and evaluations, the job responsibilities include
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) The postdoc will contribute to lab duties, which is evenly distributed among all lab members. Lab: https://www.helabucb.org/ Qualifications Basic qualifications (required at time of application) PhD
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following table(s) for the current salary scale(s) for this position: https://www.ucop.edu/academic-personnel-programs/_files/2025-26/represented-oct-2025-scales/t23.pdf . The current minimum salary range