72 algorithm-development-"St"-"St" Postdoctoral positions at NEW YORK UNIVERSITY ABU DHABI in United Arab Emirates
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Strong background in communication theory, signal processing, and wireless communications, Extensive experience in physical (PHY) layer algorithm design and performance analysis, Proven track record
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of the Water Research Center. The successful applicant will lead an innovative project focused on the development of hybrid processes for the recovery of minerals from desalination reject brine. The role will
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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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computing where the focus will be to work on to the current efforts on accelerator developments towards the HL-LHC. Expertise in trigger development, performance and optimization and/or the ATLAS computing
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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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applications for fully-funded postdoctoral research associate positions. SITE is highly interdisciplinary and aims to develop novel enabling technology on hydrodynamic stability analysis that has applications in
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to work on the development of responsive membranes with in situ switchable properties, under the supervision of Professor Nidal Hilal, Director of the Water Research Center and Global Professor
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computing where the focus will be to work on to the current efforts on accelerator developments towards the HL-LHC. Expertise in trigger development, performance and optimization and/or the ATLAS computing
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of these research will be aimed at enhanced modeling of hydraulic fracturing and carbon sequestration. The project activities will involve the development of the theory and implementation of the advanced mechanics
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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