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Field
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transformer architectures for multimodal fusion (RGB + thermal, intraoperative video, OR signals, EHR, surveys); develop temporal and cross-attention components for longitudinal risk trajectories. Build robust
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stability, reduced leakage risks, and improved energy density. This project focuses on developing efficient materials and synthesis methods that can improve ionic conductivity, battery safety, cycle life, and
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on the future as a temporal category in its comparative and political dimensions across the regional contexts under analysis. Further details are available at: https://www.anthrofuture.com . As part of
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Remote Sensing; Machine Learning Models for Predicting Wildfire Spread; Wildfire Risk Assessment Through Multi-Modal Data Integration; Automated Vegetation and Fuel Load Mapping Using Computer Vision; AI
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, New York Postdoctoral Associate: Quantifying the emerging risks of wildfire smoke for birds of North America The College of Agriculture and Life Sciences (CALS) is a pioneer of purpose-driven science
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at the intersection of active transportation safety and AI (e.g., near-miss detection, predictive crash risk, multimodal exposure estimation). · Design, implement, and validate AI pipelines (computer vision
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, 2026, with flexibility. The successful applicant will collaborate with the Pennsylvania Commission on Sentencing (PCS) on research related to sentencing guidelines, risk and needs assessment
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
); fibrin(ogen) degradation and the cellular and enzymatic drivers of thrombus resolution beyond plasminogen; and cellular and plasma mediators of FXI biology that influence bleeding risk. Additional
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 months ago
principal investigators hold faculty appointments in the departments of Nutrition and Psychology at UNC Chapel Hill. Their research interrogates nutrient roles in disease prevention, disease risk factors, and
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neurodevelopmental and mental health outcomes in children. This individual will have the opportunity to work with data from the Maternal and Developmental Risks from Environmental and Social Stressors (MADRES) cohort