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research on the design and development of next-generation wireless communication systems. Specific topics include, but are not limited to, waveform design for the THz spectrum under hardware constraints
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Associate Research Scientist / Post-Doctoral Associate in the Division of Science (Computer Science)
to develop applied research skills in machine learning, interact with an international network of collaborators, and gain post-doctoral research experience. The ideal candidate is self-motivated and can work
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Description The Water Research Center at New York University Abu Dhabi seeks to recruit a Post-Doctoral Associate to develop calix[n]arene-based covalent organic frameworks for water purification
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learning, and AI-driven manipulation. This position offers the opportunity to work on real-world robotic systems and develop novel algorithms at the intersection of robot learning, control, and AI
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to contribute to the intellectual property development through patent filings, as well as participating in standardization efforts relevant to wireless technologies, in coordination with academic and industrial
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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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work experience with some quantum machines and development environments like QiSKit and PennyLane are highly appreciated. The selected candidate will work on cutting-edge technologies in an excellent
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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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development of cognitive omni-band wireless systems for 6G and beyond. The successful candidate will be jointly supervised by Mahmoud Rasras and Murat Uysal and will work in close collaboration with other
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Post-Doctoral Associate in Sand Hazards and Opportunities for Resilience, Energy, and Sustainability
management. Develop and validate computational models for monitoring and predicting infrastructure performance. Collaborate with faculty and researchers across SHORES. Disseminate research findings through