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Field
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with physics-informed neural networks, automatic differentiation, neural ODEs, or other physics-aware DL techniques. Skill in programming languages such as Python, C/C++, Go, Rust etc. Ability to model
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& Perception Laboratory (NA&P Lab), led by Dr. Sabine Kastner at the Princeton Neuroscience Institute. The lab studies neural mechanisms of cognition in the primate brain. Intracranial recordings from human
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technological developments/trends in robotics/controls/communication and networking/modeling/machine learning/ neural networks. Salary will be commensurate with qualifications and experience. An offer
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systems), Mathematical biology (Dynamics of ecosystems, Animal movement, Epidemic processes, Forest fires, Biological evolution, Modeling based on Machine Learning and Neural Networks), Socio-economic
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learning problems involving a-priori known symmetries. A simple example are convolutional neural networks, that are known to be invariant towards translations. Using representation theory, one can build
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preferred: the development of computational models to represent structural performance using commercial and research software tools the development and validation of neural network models focused
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to Professor Bas Rokers. Linking Retinal, Neural, and Perceptual Deficits in Visual Disorder: Individuals in the UAE are at substantial risk for perceptual deficits due in part to one of the highest diabetes
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, cancer biology, genetics, biostatistics, neuroscience, immunology, and behavioral medicine and interventions, offering research opportunities focusing on the interactions of genetic, molecular, neural
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Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
to develop hybrid models for sea ice that combine coupled climate models and machine learning. Our previous work has demonstrated that neural networks can skillfully predict sea ice data assimilation
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experience in at least one of the following topics: deep learning, reinforcement learning, probabilistic modeling, statistical learning, neural networks, or other related fields Interest in interdisciplinary