66 algorithm-development-"Multiple"-"Simons-Foundation"-"Prof"-"UNIS" Postdoctoral positions in United Arab Emirates
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processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large
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inequalities Markov processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic
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for urban networks, bridge the gap between scientific significance and practical value, and further develop the human capital to propel the city of Abu Dhabi and the UAE into a more prosperous and sustainable
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Description The Water Research Center at New York University Abu Dhabi seeks to recruit a postdoctoral associate to work on the development of responsive membranes with in situ switchable properties
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the supervision of Dr Daniel Johnson, Assistant Professor of Engineering and Co-PI of the Water Research Center. The successful applicant will lead an innovative project focused on the development of hybrid
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, the candidate will develop polymeric lubricious coatings for catheters to minimize injury to blood vessels during the trans-catheterization process. They will characterize the surface modifications of implants
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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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on Macro, Labor and/or Development Economics. The appointment is for 2 years and will begin September 1, 2026, subject to final budget approval and UAE visa acquisition by the prospective post-doctoral
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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