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Field
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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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present research findings at regional and national conferences. Qualifications: A PhD in Chemistry, Materials Science and Engineering, Physics, Nanoscience and Nanoengineering or equivalent is required
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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
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% for PhDs and TV-L E14, 100% for PostDocs; 45k - 57k Euro / year + benefits). For interns, we offer a stipend to cover living expenses. Click here to learn more about our research. Topic / Area: The
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: The candidate must have a PhD and extensive experience in modern deep neural network-based techniques. The ideal candidate should have: A PhD and a strong record of research or applied work in deep learning, with
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imaging, genetics, omics, EHR data, and clinical outcomes. Ongoing work builds on deep-learning phenotypes from cardiovascular imaging at population scale and extends toward myocardial tissue remodeling
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appointed through the Office of Postdoctoral Affairs. The FY27 minimum is $79, 056. Precision mapping of vector borne diseases using deep learning & high resolution remote sensing data Faculty in Stanford