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Postdoctoral Fellow to advance cutting-edge research at the intersection of artificial intelligence (AI), natural language processing (NLP), digital health, and health equity. This position is funded by the UBC
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Kunsthistorisches Institut in Florenz - Max Planck Institute, Berlin, Germany | Germany, | Germany | 3 months ago
, artificial intelligence, the digital transformation, and the future of museums. 4A_Lab connects disciplines, collections and institutions. It attempts to foster dialogue and exchanges between disciplines, and
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. Expertise in artificial intelligence and machine learning. Recent research experience in the development of first-principle wave models. Recent research experience in the development of numerical codes
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established a position for a Postdoctoral Researcher focused on work at the intersection of artificial intelligence and Responsible AI, NLP & IR 3.0, Health/Wellness, and/or Life Sciences. The Postdoctoral
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will join Andrej Prša’s research team and work on the PHOEBE code , developing the modeling proxy based on artificial intelligence (AI). The goal of the AI-powered model is to enable the autonomous
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A postdoctoral fellow position is available in Haiming Cao’s laboratory in the Cardiovascular Branch of the National Heart, Lung, and Blood Institute (NHLBI), NIH. The Cao lab integrates artificial
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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | 21 days ago
artificial intelligence applications in drug development. You will gain experience researching advanced in silico prediction algorithms, analyzing machine learning approaches for toxicity pattern recognition
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national research agenda of strategic value. Research Fields for applicants: The Digital Age: Artificial Intelligence, Smart Systems, and Data Science; Sustainable Future: Green Technologies and Circular
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and weaknesses for end-users. Help develop new or improve existing soil moisture estimates using NISAR and other datasets utilizing artificial intelligence (AI) and machine learning. The outcome from
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science and artificial intelligence to understand the time-course of naturalistic scene understanding. We are especially excited about applicants who enjoy: (1) working with large, real-world datasets, (2