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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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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
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supporting better patient outcomes. The successful candidate will lead the development of multi-modal MRI foundation models that integrate imaging data and radiology reports. Using advanced deep learning
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description You will be contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will
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lead the development of multi-modal MRI foundation models that integrate imaging data and radiology reports. Using advanced deep learning techniques—including vision-language architectures (e.g., CLIP
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topics: Free space optical communication Visible light communication DSP for coherent optical communication Machine learning and AI-native physical layer design Optical reconfigurable intelligent surfaces
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Requirements Applicants must hold a PhD degree in Machine Learning, Artificial Intelligence, Computer Science, Statistics, or a closely related field. A strong research background and programming experience
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from varied sources, and machine learning methodologies. The underlying data are complex and will require sophisticated data management and integration skills. A candidate should have proficiency with
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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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their work. Qualifications: PhD in Electrical and Computer Engineering, Biomedical Engineering, Mechanical Engineering or a related field. A combination of education and relevant experience from which