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19.07.2022, Academic staff The Machine Learning and Information Processing group at TUM works in the intersection of machine learning and signal/information processing with a current focus on deep
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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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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
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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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modeling, satellite remote sensing, or machine learning Programming skills (Python or R) Strong publication record
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National Aeronautics and Space Administration (NASA) | Huntsville, Alabama | United States | about 4 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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humanities disciplines. Familiarity with contemporary AI systems (e.g., machine learning, generative models) at a conceptual or applied level. Experience with qualitative or mixed research methods (e.g
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the Chemistry Department of NYU is seeking to recruit one postdoctoral associate interested in working on synthesis of complex natural products or new methodology development. This position is based in New York
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | 23 days ago
data analysis methods to study biological memory circuits and their applications to machine learning. Building on recent work from the Fiete Lab, the role focuses on identifying principles of biological
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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