119 software-testing-short-course Postdoctoral positions at NEW YORK UNIVERSITY ABU DHABI
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: The development of computational models to represent structural performance using commercial and research software tools The development and validation of machine learning and artificial intelligence models focused
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software tools The development and validation of machine learning and artificial intelligence models focused on representing the structural response Physical experimental testing for structural and
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: The development of computational models to represent structural performance using commercial and research software tools The development and validation of machine learning and artificial intelligence models focused
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must have a PhD in Geotechnical Engineering, or a related field with a focus on one or more of the following: Centrifuge experimental testing (design, execution, and data interpretation) Numerical
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: massive MIMO, near-field propagation, channel estimation. Experience working with software defined radios and experimental testbeds for wireless communications systems. Applications will be accepted
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: The development of computational models to represent structural performance using commercial and research software tools The development and validation of machine learning and artificial intelligence models focused
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qualifications, it is desirable that the applicants have: Research background in one or more of the following areas: massive MIMO, near-field propagation, channel estimation. Experience working with software
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. The job also emphasizes the dissemination of knowledge about population health, particularly through the preparation of peer-reviewed manuscripts, software packages and/or participation in international
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/optical ray tracing simulation software, e.g., Wireless Insite, Zemax Proven track record of publications in relevant IEEE journals and conferences The candidates will be considered until the position is
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. The group will be contributing to the Physics Modeling (MC software, MC validation and Pileup modeling), the MET High-Level Trigger validation, optimization and performance studies, and to the heterogeneous