28 developer-"https:"-"https:"-"https:"-"European-Commission" positions at NEW YORK UNIVERSITY ABU DHABI
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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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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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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 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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opportunity to shape a dynamic academic division at a pivotal moment in the university’s evolution. The Dean will lead a vibrant community of scholars who advance foundational and applied research on some of
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environments, hardware platforms, and frequency bands Develop, validate, and document ISAC channel modeling methodologies tailored to the lab’s hardware/software testbed. Integrate SDRs (e.g., USRPs, RFSoC) and
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Responsibilities The PDA will conduct research to design and develop optical wireless communication systems. This involves the development of mathematical models for signal transmission/reception, derivation
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candidate is expected to take a leading role in the development of the group tasks and help in supervising PhD students. Applicants must have a PhD in theoretical high energy physics or related field
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initiative focusing on designing and developing novel medical devices for ultimate human use. Laboratory for Advanced Neuroengineering and Translational Medicine oversees a variety of exciting projects
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related to materials. The successful candidate will independently lead a project focused on developing generative AI models to establish structure-property relationships for materials discovery