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Field
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Engineering program of the Engineering Division and the Center of Artificial Intelligence and Robotics at NYU Abu Dhabi the group of Prof. Kostas J. Kyriakopoulos seeks to improve the autonomy of Field Robotic
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on nuclear arms control, disarmament, nonproliferation, verification, and on the global security challenges associated with emerging technologies such as artificial intelligence, quantum technologies, and
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artificial intelligence (AI). About us The Institute of History and Ethics in Medicine (IHEM) is part of the School of Medicine and Health at the Tech-nical University of Munich. At the Institute of History
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of artificial intelligence (AI) into real-time data analysis. This integration can revolutionize the interpretation of remote sensing data, allowing for rapid decision-making in critical situations, such as
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of natural language processing, machine learning, artificial intelligence, and human-computer interaction. Established within the School of Computer Science, LTI pioneers innovative approaches to understanding
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methodologies and international collaborations. Developing novel computational tools that use recent advances in artificial intelligence to automate and enhance bioinformatic analyses. These projects
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accelerate translational research. Build or leverage novel artificial intelligence and machine learning (AI/ML) techniques for advanced liquid biopsy (ctDNA) and tissue transcriptomic (RNA-seq) data to predict
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-based solutions to societal challenges. We have a long-term involvement in applied and interdisciplinary research, big data and data science, artificial intelligence (AI), the Internet of Things (IoT
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Description As part of the Electrical Engineering program of the Engineering Division and the Center of Artificial Intelligence and Robotics at NYU Abu Dhabi the group of Prof. Kyriakopoulos seeks
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projects and publications from the group can be found here: https://www.kcl.ac.uk/research/pavri-group About the role The project is focused on combining artificial intelligence (AI)-based machine learning