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, Pandas, SciPy, scikit-learn, PyTorch, TensorFlow) Experience developing and deploying machine learning or deep learning models Ability to present complex results to multidisciplinary teams, including
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associate will work both independently and collaboratively to develop and apply novel deep learning algorithms and/or computational chemistry methods for small-molecule drug discovery targeting RNA
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computer vision tools (e.g., MediaPipe, OpenPose, homography estimation, optical flow). Experience with eye-tracking data collection or analysis. Familiarity with deep learning frameworks (PyTorch
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, research, and public service. Purpose: The Postdoctoral Researcher will work on research projects in the area of wireless communication system design with machine learning applications. The ideal candidate
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learning (RL) and deep reinforcement learning (DRL) for autonomous process management, dynamic resource distribution, and real-time decision-making. Design and deploy digital twins for integrated chemical
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motivated and talented postdoctoral research associate(s) to join our dynamic team. This role lies at the exciting intersection of High-Performance Computing (HPC) and Artificial Intelligence (AI) at scale
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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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and other postdoctoral researchers as part of our Lundbeck Professorship grant, which you can learn more about here: https://www.cnap.hst.aau.dk/lundbeck-professorship As a postdoctoral researcher your
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
. Preferred Qualifications, Competencies, and Experience Programming skills (e.g., python, bash scripting, Fortran, C++ and CUDA), expertise in computational modeling (such as Deep Learning, Molecular Dynamics
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Experience with deep learning frameworks such as PyTorch or TensorFlow Exposure to AI-enabled scientific workflows that couple simulation with data-driven modeling, including emerging approaches involving