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At the heart of SIT’s mission is to nurture industry-ready graduates equipped with deep technical expertise and transferable skills to tackle tomorrow’s challenges. SIT collaborates with industry in
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research at the intersection of AI/deep learning, bioinformatics, mathematical modeling, computational topology, scientific machine learning, for systems biology, single-cell genomics and protein design. The
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Current Employees: If you are a current Staff, Faculty or Temporary employee at the University of Miami, please click here to log in to Workday to use the internal application process. To learn how
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-Based Wildfire Smoke and Air Quality Monitoring; Deep Learning for Post-Wildfire Damage Assessment. PROFILE of the OFFICE OF POSTDOCTORAL AFFAIRS (OPA) The mission of the UNLV Office of Postdoctoral
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or more of the following areas: Reinforcement Learning / Deep Reinforcement Learning Fine-tuning and Application of Large Language Models Time-Series Data Prediction and Modeling Intelligent Decision-Making
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U.S. Department of Energy (DOE) | Washington, District of Columbia | United States | about 12 hours ago
receive hands-on experience that provides an understanding of the mission, operations, and culture of the DOE. As a result, fellows will gain deep insight into the federal government's role in the creation
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of innovation and tradition. Renowned for hands-on learning and pioneering research, Mines educates future leaders in STEM fields who will make a meaningful impact on the world. Our vibrant community
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) conferred by start date Demonstrated experience with imaging and/or video datasets Training and experience in machine learning, computer vision, and deep learning methods Excellent English language
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), and in vivo fiber photometry (TDT). We are particularly looking for a PhD-level systems neuroscientist with expertise in animal behavior tracking using deep learning algorithms and their causal link
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of the appointment. Demonstrated experience with deep learning methods or sophisticated mathematical frameworks applied to large-scale or scientific datasets. Experience working with observational seismology data (e.g