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recognizers, chatbots based on both procedural rules and learning from a text corpus, and build classifiers with neural networks. Mission Statement The mission of the University of Michigan is to serve
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earthquake engineering; various AI-methods, such as artificial neural networks (including causal, convolutional, deep, recurrent, physics-guided), genetic algorithms, random forests, classical and symbolic
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incorporating context from additional data such as wireline logs or well reports. You are suited for this position if you are highly motivated, have interests in computer vision and neural networks, and want
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analysis in medicine. Experience of software version control with Git, typesetting with LaTeX, use of Linux computers; Experience with graph-based methods, and graph convolutional/neural networks; Experience
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in several tasks within the project’s work plan, including: - Development of deep learning models (e.g., convolutional neural networks and vision transformers); - Presentation of results at consortium
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learn a monolithic, “black-box” world model, often using a large neural network as function approximators. While these models can be highly effective for prediction within their training distribution
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Groups: This position will work with two different laboratory groups. The first group is an interdisciplinary group exploring capabilities of artificial intelligence (AI) on different fields such as
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learning. Theoretical areas of interest include (but are not limited to) optimization, neural networks, and reinforcement learning. Application areas of interest include (but are not limited to) robotics
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interdisciplinary areas. Research fields of particular interest include, but not limited to: biomedical science and engineering veterinary science computer science and data science neuroscience and neural
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improve data analysis techniques, e.g., goal selection, analysis of decision variables, and artificial neural networks. 7. Applicable legislation and regulations: Research Fellow Statute (EBI), approved by