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, convolutional and recurrent architectures, and transformer-based models, as applicable to biological, imaging, and multimodal data Hands-on experience with machine learning and deep learning frameworks (e.g
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cutting-edge research in areas such as pattern recognition, automation science, complex systems, AI for Science, robotics, machine learning, computer vision, natural language processing, biometrics, medical
Searches related to image processing and machine learning
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