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Field
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The Argonne Leadership Computing Facility’s (ALCF) mission is to accelerate major scientific discoveries and engineering breakthroughs for humanity by designing and providing world-leading computing
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-world problems in the fields of Biology, Health, and Engineering. An effective research program will execute use-inspired discovery with an entrepreneurial mindset that develops science and solutions
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international and regional leadership in biostatistics, genomics, biomedical informatics, artificial intelligence and health data science. We are recruiting a creative, rigorous Postdoctoral Research Scientist
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program investigating gut immune dysfunction, epithelial barrier disruption, microbiome-driven inflammation, and intestinal injury following burn trauma, colitis, and critical illness. Position Overview
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Focus on Active Transportation Safety & Artificial Intelligence (AI) Position Details Position Description Position Description The School of Engineering & Technology (SET) at the University of Washington
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employ a range of approaches, including quantitative and computational methods, ethnography, and field- and lab-based research. Interdisciplinary exchange is central to our work, and our collaborations
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: electrodeposition, electrocatalysis, electrochemical synthesis, metallurgy, or corrosion Experience with high-temperature or molten salt electrolyte systems Track record of integrated computational and experimental
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 months ago
Intelligence, Computational Biophysics and Chemistry, and Drug Discovery. The successful candidate will contribute to the development of novel theoretical and computational methods as well as advanced AI
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intelligence methods (ML/AI) for diverse biological data in relation to cardiovascular and neurodegenerative diseases. The specific areas of methodological research can be flexible, depending on the candidate’s
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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