30 algorithm-development-"Prof"-"Prof"-"Prof" Postdoctoral positions at NEW YORK UNIVERSITY ABU DHABI
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, climate, and human health. Examples of current active projects include: Developing optimization models to analyze and mitigate fine particulate matter (PM2.5) exposure from various infrastructure systems
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the connections between accretion and ejection. 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
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Postdoctoral Associate to work on a fascinating project focused on the development machine-learning powered digital twin system for the structural performance of civil engineering structures. The project is a
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: Investigating membrane fouling mechanisms and mitigation strategies in desalination and water treatment processes. Developing and optimizing functional membranes, including electrically conductive membranes
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to work on various research projects on developing resilient and sustainable construction materials. The successful candidate will work on advancing the development and characterization of reactive
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Description The Center for Smart Engineering Materials (CSEM), New York University Abu Dhabi,seeks to recruit a post-doctoral associate to work on the development, characterization, and applications
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involved in the development of open source tools and resources, and to work on publications related to their work. CAMeL's mission is research and education in artificial intelligence, specifically focusing
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the supervision of Professor Nidal Hilal, Director of the Water Research Center and Global Professor of Engineering. The successful applicant will drive an exciting project on developing functional membrane
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on accelerator developments towards the HL-LHC. Expertise in trigger development, performance and optimization and/or the ATLAS computing model is preferred. The selected candidate will work in the ATLAS
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the eye and brain that explain vision loss, building on our previously-developed method linking clinical, neural and behavioral data (Allen et al., 2018; Miller et al., 2019; Pedersini et al., 2023). We