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collaborative and open environment? If so, the Oak Ridge National Laboratory’s Learning Systems Group within the Data and Artificial Intelligence Systems section invites you to apply to our new postdoctoral
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Research, and Meta. Responsibilities: The Postdoctoral Fellows will be responsible for leading ongoing innovative research projects. Examples include: The development of probabilistic deep learning models
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of faculty at SUNY Polytechnic Institute and the University of South Florida, consisting of mathematicians, physicists, computer scientists, and engineers investigating applications of deep learning
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and methods for advancing the research effort Design and carry out computer experiments on deep learning and related robotic simulations Collaborate with other engineers to create prototypes of embodied
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Posting Details Posting Details Logo Institution South Dakota Mines Working Title Postdoctoral Researcher Posting Number NFE02879P Department SDSMT-Nanoscience and Nanoengineering 1 Physical
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are proficiency in Python, deep learning frameworks such as Keras, PyTorch, TensorFlow, or other related software stacks, and a solid background in machine learning, cybersecurity, or AI robotics, and the ability
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Posting Details Posting Details Logo Institution South Dakota Mines Working Title Postdoctoral Researcher Posting Number NFE02891P Department SDSMT-Physics 1 Physical Location of Position (City
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closely related field. Required Skills : Proficiency in Python/C and familiarity with at least one deep learning framework (e.g., PyTorch, TensorFlow, or Keras). Interest in or prior experience with
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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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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 12 days ago
looking for a postdoctoral fellow interested in developing either machine learning algorithms for high-resolution histopathology imaging/spatial-profiling data in combination with other modalities (e.g