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Field
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English, both spoken and written. Additional experience that would be considered a plus: - some experience in programming and the use of computer algebra in algebraic geometry; - experience with
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artificial intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human-computer interaction, social networks, fairness, and data ethics. Our research is rooted in basic
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journals and conferences. This role provides a unique opportunity to work with the world’s first exascale system, Frontier, and collaborate with leading experts in machine learning, optimization, electric
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data from both tissue and single cells, for improved understanding of Alzheimer progression. Experience in brain disorders, machine learning and deep learning will be a plus. Interested candidates should
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CO2 capture from the atmosphere. Your objectives will include to: Develop new optimization and/or machine-learning based reconstruction and segmentation algorithms to improve image quality in time
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. The appointee will primarily conduct research applying advanced machine learning/AI (including techniques like deep learning) to analyze complex biological and clinical data (e.g., single-cell multi-omics
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the pre- and post-processing of Magnetic Resonance (MR) images (or utilization of existing brain imaging markers), taking peripheral or central biomarkers, and regressing them against those images using
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also include technique development work aimed at combining imaging techniques and data analysis to provide a more integrated picture of life processes in the context of health and disease. To be a
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. The processes involved in triggering outbursts, using optical monitoring and the real-time pipeline X-ray Binary New Early Warning System (XB-NEWS) developed at NYUAD, and comparisons to AGN and other compact
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4D flow imaging, proficiency in machine learning applications relevant to neuroimaging, familiarity with fluid dynamics and its application to physiological data, and ultrasound imaging is desired