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the HIV Vaccine Trials Network supported by the NIH Division of AIDS and the Vaccine & Immunology Statistical Center (VISC), supported by the Gates Foundation we are leading major computational efforts
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scholars appointed through the Office of Postdoctoral Affairs. The FY27 minimum is $79, 056. Position Overview and Scientific Vision The laboratory of Dr. Sohail Husain in the Stanford Pediatric Exocrine
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broader university. The Postdoctoral Research Associate will be responsible for conducting field, laboratory, and/or computer modeling studies to address research questions in the Geological and/or
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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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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 21 hours ago
research outputs and an important reason why Carolina is one of the leading public research institutions in the country. UNC-Chapel Hill offers postdocs comprehensive medical and vision coverage , paid leave
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with eBeam, X-ray, and gamma radiation-treated blow flies. - Evaluate, select, and apply standard techniques of routine research; keep detailed records of data. - Use computers and laboratory
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comprehensive benefits package designed to enhance health, well-being, and financial security. Benefits include medical/vision, dental, flexible spending accounts, life, disability, retirement, family life
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in the field of network science, with applications to nutrition, biological networks, network medicine, and the science of science. The position involves developing and applying computational
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. QUALIFICATIONS PhD in Civil Engineering, Environmental Science, Computer Science, or a related field Research experience in hydrology, geospatial analysis, and machine learning Skills of scientific writing and
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research program in Artificial Intelligence (AI) and Mathematics. This position involves applying machine learning tools, particularly reinforcement learning (RL), to address complex research-level