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and spatiotemporal scales, i.e., new forms of real-time automation of intelligent active grids including grid-forming converters, using distributed control and artificial intelligence (AI) based
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challenge. This project aims to explore data-driven Artificial Intelligence/Machine Learning (AI-ML) approaches to meeting this challenge. Possible topics include, but are not limited to: storylines
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and aggression, using optogenetics, in vivo imaging, electrophysiology, and sophisticated machine learning/artificial intelligence analyses of mouse behavior. All projects have translational components
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for Artificial Intelligence. Strong demonstrated programming skills including Python or other similar languages. Ability to work independently, prioritize tasks, and deliver results in a timely manner. Assess and
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. By combining methods from human-computer interaction, clinical informatics, and artificial intelligence, we aim to create systems that enhance reasoning, surface relevant information at the bedside
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understanding of artificial intelligence applications and methodologies, such as working knowledge of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI
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., transcriptomics, proteomics, metabolomics) and artificial intelligence/machine learning (AI/ML) applications in biomedical research will be considered a strong advantage. Outstanding UA benefits include health
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Digital Economy Lab Human-Centered Artificial Intelligence Computer Science Postdoc Appointment Term: 2 years Appointment Start Date: ASAP Group or Departmental Website: https://digitaleconomy.stanford.edu
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submit papers to top journals in statistics, and top conferences in machine learning, statistics, and artificial intelligence. The candidates will also present their research at conferences in these fields
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We are seeking a highly motivated Postdoctoral Researcher with expertise in computational biology, deep mutational scanning data, and generative artificial intelligence (AI). The successful