16 phd-computer-artificial-machine-human "https:" Postdoctoral positions in United Arab Emirates
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: The development of computational models to represent structural performance using commercial and research software tools The development and validation of machine learning and artificial intelligence models focused
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working at the intersection of machine learning, algorithmic fairness, human-computer interaction, and responsible AI. The project aims to investigate how bias emerges in data pipelines and AI systems
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-relationships, materials optimization, materials under extreme conditions, and generative AI. Candidates must possess substantial experience in artificial intelligence and machine learning methods, specifically
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research team working at the intersection of machine learning, algorithmic fairness, human-computer interaction, and responsible AI. The project aims to investigate how bias emerges in data pipelines and AI
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of Artificial Intelligence and Robotics at NYU Abu Dhabi the group of Prof. Kostas J. Kyriakopoulos seeks to improve the autonomy of Field Robotic systems by fusing control theoretic and machine intelligence
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, artificial intelligence, computer vision, robotics, UAVs, etc. is a plus. Other preferred qualifications include: expertise in programming and coding (preferably using Python and C++) and GUI development
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-relationships, materials optimization, materials under extreme conditions, and generative AI. Candidates must possess substantial experience in artificial intelligence and machine learning methods, specifically
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learning and artificial intelligence Bachelor’s/ Master’s degree in computer science, mathematics, computer engineering, or relevant technical field First-author peer-reviewed published papers (or under
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: The development of computational models to represent structural performance using commercial and research software tools The development and validation of machine learning and artificial intelligence models focused
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research team working at the intersection of machine learning, algorithmic fairness, human-computer interaction, and responsible AI. The project aims to investigate how bias emerges in data pipelines and AI