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intelligence, and multimodal learning. The main objective of this position is to develop novel generative AI methods for computer vision applications, with a particular focus on Diffusion Models and Vision
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track record in neurobiologically mechanistic modeling (i.e., models should incorporate known neurobiology and neurophysiology, rather than relying on black-box machine learning approaches
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National Aeronautics and Space Administration (NASA) | Huntsville, Alabama | United States | about 10 hours ago
to advance use of foundation models for Earth Science research and applications, including fine-tuning experiments Use of remote sensing, models, and/or machine learning to further our understanding
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issues. Proficiency in urban modeling tools such as MATLAB, Python (especially libraries like Pandas, NumPy, SciPy, GeoPandas, etc.), and R. Advanced skills in predictive modeling and machine learning
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applications for a fully funded postdoctoral associate position. This position, available immediately, focuses on developing machine learning and deep learning methods for analyzing large-scale single-cell DNA
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Job Title Postdoctoral Research Associate Agency Texas A&M University Department School of Engineering Medicine Proposed Minimum Salary Commensurate Job Location Houston, Texas Job Type Staff Job
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at other institutions. The International Union, United Automobile, Aerospace and Agricultural Implement Workers of America (UAW) is the exclusive representative of the postdoctoral scholars. https
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field Experience leveraging artificial intelligence or machine learning in the development of battery electrolytes and catalyst materials Demonstrated expertise in lithium–sulfur battery materials and
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Classification Title: Postdoctoral Associate Classification Minimum Requirements: Ph.D. and/or MD in an appropriate scientific discipline required. Job Description: The Makino Laboratory is seeking
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on studying the principles of neural computation through recurrent neural networks, dynamical systems theory, and machine learning. - Develop mathematical and computational models of neural networks - Analyze