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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 4 hours ago
, reinforcement learning, and computational game theory to address this gap. Fellows will contribute to advancing the next generation of models, algorithms, and system architectures for autonomous systems, multi
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. This is primarily for an NIH-funded project developing multimodal variational autoencoder models and probabilistic trajectory analyses for latent spaces formed from neural, genetic, and behavioral data
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analyses for latent spaces formed from neural, genetic, and behavioral data. Mission Statement Michigan Medicine improves the health of patients, populations and communities through excellence in education
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with applications to aerospace systems Designing, implementing, and testing control algorithms in simulation and hardware platforms Contributing to publications and reports; presenting research findings
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and Machine Learning, with a focus on studying geometric structures in data and models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees
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Abrahao (NYU Shanghai) and João Sedoc (NYU Stern). Research Focus Areas Our research encompasses topics in DL and AI, including but not limited to: Deep Learning Algorithms and Paradigms Generative Models
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algorithm development, data analysis and inference, and image analysis Ability to do original and outstanding research in computational biology, and expertise in computational methods, data analysis, software
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algorithm development, data analysis and inference, and image analysis Ability to do original and outstanding research in computational biology, and expertise in computational methods, data analysis, software
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-photonic computing architectures; Silicon-photonic network architectures Machine Learning Algorithms/Systems: Experience in design and use of ML algorithms; Experience in using ML for designing computing
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applying interpretable AI / machine learning / deep learning / information-theoretic methods and algorithms in the context of multiscale biological networks, ranging from molecules (protein chemistry) to