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complementary data from other Mars missions to strengthen current models and provide comparative insights that enhance research conclusions from Hope observations. Develop Machine Learning methods and run
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comparative insights that enhance research conclusions from Hope observations. Develop Machine Learning methods and run numerical simulations on NYUAD’s High-Performance Computing (HPC) system. Support
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exploring new modes of human-computer interactions. Has demonstrated experience in exhibiting works and/or presenting at festivals and conferences, with the ability to teach and support students in developing
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or willingness to learn quickly. Publications, thesis work, or demonstrable projects in computer vision, multi-modal ML, digital twins or biomedical ML. Familiarity with uncertainty quantification and model
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(SHORES) and the Division of Engineering, New York University Abu Dhabi, seek to recruit a Postdoctoral Associate to work on a fascinating project focused on the development machine-learning powered digital
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seeks to appoint an Associate Research Scientist. Motivated applicants with a strong background in Machine Learning, Robotics, Haptics, and interest in leading cross-disciplinary research to study
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teaching faculty to teach an undergraduate course, Machines that Create, an introductory yet comprehensive overview on Generative AI and Foundation Models, covering the methods and techniques driving modern
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particular, we want to use machine learning/deep learning to achieve this. Currently, a basic automatic optimization module that relies on machine learning has been developed and we want to take that module
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at the intersection of artificial intelligence and cultural heritage. The successful candidate will be involved in cutting-edge research and development in 3D computer vision and machine learning for the digital
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developing new machine learning methodologies that tackle unique computational problems in healthcare applications. We use large real-world complex datasets, including data extracted from electronic health