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machine/deep learning, computer vision, or applied statistics. Solid programming skills in Python and experience with deep learning frameworks (e.g., PyTorch or TensorFlow) Project funding Other Funding
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experience with R, MATLAB, or Julia is an advantage. Machine Learning Expertise : Familiarity with causal machine learning, ensemble methods, and deep learning architectures (CNNs, RNNs). Experience
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, including the ultra-high-resolution Energy Exascale Earth System Model (E3SM), the machine learning emulators ACE-ERA5 and ACE-E3SM, and the regional Energy Research and Forecasting (ERF) model. The work
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effect. Bhat group The position will involve developing new mathematical/computational methods at the intersection of scientific computing and machine learning. At a high level, the project is to
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 18 hours ago
Chapel Hill seeks a talented, highly motivated postdoctoral researcher with a background in machine learning and/or biomedical image processing. The ACM Lab is developing software to support AI-driven
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Challenge grant. The successful candidate will work closely with the Principal Investigators (PIs) to develop and implement innovative research integrating machine learning, computer vision, and
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The Ohio State University | about 2 months ago
skills using modern languages such as Python or C++. Expertise in statistical analysis, machine learning, and data-driven modeling is highly desirable. Appointment is contingent on the university’s
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(Ithaca, NY) is seeking a creative, computationally driven Postdoctoral Associate to help invent the next generation of liquid biopsy technologies. The De Vlaminck Lab ( https
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Group or Departmental Website: https://ashleylab.stanford.edu/ (link is external) How to Submit Application Materials: Email CV to Bruna Gomes @ [email protected] (link sends e-mail) Does this
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flexible; applications will be reviewed on a rolling basis until the position is filled. Group or Departmental Website: https://resilientfutures.stanford.edu/ (link is external) How to Submit