57 computational-physics-superconductor Postdoctoral positions at NEW YORK UNIVERSITY ABU DHABI
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machine learning. The successful applicant will participate in research involving human computation, knowledge discovery, machine learning, and data science. The position will provide the opportunity
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Description The New York University Abu Dhabi Computational Approaches to Modeling Language (CAMeL) Lab seeks to hire a post-doctoral researcher to work in any of the lab research areas, to be
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Description NYUAD Experimental High Energy Physics group is searching for a post-doctoral associate to join the planned group's efforts to be involved in the ATLAS experiment as part of the UAE
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competitive salary and benefits. Research in the SIT-D lab focuses on understanding and modelling consumers' behavior and decision process for sustainable transport modes and transport innovations. Research is
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for physical systems. The postdoc will work on projects focusing on one or more of the following: Robot Learning & Autonomy – Developing algorithms that allow robots to learn (via exploration or imitation) from
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, machine-learning model development, structural sensing and health monitoring, conducting physical experiments, and validation of computational models. Required Qualifications: A successful applicant must
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Description The newly established NYUAD Wireless Research Center at New York University Abu Dhabi, seeks to recruit a Post-Doctoral Associate (PDA) who will conduct research on the physical layer
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Description The newly established NYUAD Wireless Research Center at New York University Abu Dhabi, seeks to recruit a Post-Doctoral Associate (PDA) to engage in cutting-edge research on the physical
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on the physical layer and MAC layer design for wireless systems, particularly across multiple spectrum bands. The PDA is expected to actively disseminate results through publications in high-impact journals and
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the research team of Prof. M. Umar B. Niazi. The position focuses on the development of digital twins using physics-informed learning approaches, with specific applications to intelligent transportation