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Field
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statistical approaches. A fundamental understanding of Deep Neural Networks as applied to high-frequency time series datasets, including the ability to design and implement custom NN models in PyTorch, as
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platforms, as well as extensive networking opportunities within the University of Miami’s robust AI and digital health ecosystem. Program Objectives: Provide fundamental training by interdisciplinary faculty
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. Ideally, we would like to know the cochlear output precisely to study its effect on neural representations. However, because cochlear mechanics and neuronal processing are reciprocally coupled through
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of improving human health. Aligned with Rutgers University–New Brunswick and collaborating university wide, RBHS includes eight schools, a behavioral health network, and five centers and institutes that focus
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dynamics enabling naturalistic animal behavior? Our labs aim at building mechanistic models of brain function grounded in a combination of theoretical approaches, neural network-based simulations, and
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learning methods. Develop deep learning architectures (e.g., variational autoencoders, graph neural networks, transformers) for cross-omics data representation and feature extraction. Apply multi-view
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interpretable deep neural networks is required. Candidate must have published in top journal and conference at least one scientific paper in interpretable machine learning (not explanations of black boxes) among
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human health. Aligned with Rutgers University–New Brunswick and collaborating university wide, RBHS includes eight schools, a behavioral health network, and five centers and institutes that focus
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spared from injury into personalized musculoskeletal models to enable robust neural control of robotic assistance in stroke survivors. Real-time characterization of the effect that electrical stimulation
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geometric understanding of training in deep neural networks. The position offers excellent training opportunities at the intersection of machine learning and applied mathematics. Qualifications: - Applicants