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, telecommunications or related field. Other requirements include Strong background in communication theory, signal processing, and wireless communications, Extensive experience in physical (PHY) layer algorithm design
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on subjects including (in no particular order): Random Matrix Theory Free Probability Functional and concentration inequalities Mixing times of Markov chains While excellent candidates with other research
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, United Arab Emirates [map ] Subject Area: Probability theory Appl Deadline: none (posted 2025/10/01) Position Description: Apply Position Description The Division of Science at New York University Abu
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, starting Fall 2026 to work under the supervision of Prof. Pierre Youssef on subjects including (in no particular order): Random Matrix Theory Free Probability Functional and concentration inequalities Mixing
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associate to work on one or more of the following topics: Mathematical Physics, Spectral Theory, Quantum Chaos, Large Graphs and Quantum Walks. Related areas such as Quantum Information can also be considered
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motivated post-doctoral associate with a strong background in game theory, control systems, and/or learning theory to join the research team of Prof. Muhammad Umar B. Niazi. The position focuses on the design
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, telecommunications or related field. Other requirements include Strong background in communication theory, signal processing, and wireless communications, Extensive experience in physical (PHY) layer algorithm design
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: Strong background in communication theory, signal processing, and wireless communications Proven track record of publications in relevant IEEE journals and conferences Extensive experience in physical
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. This involves the development of mathematical models for signal transmission/reception, derivation of performance limits, algorithmic-level system design and performance evaluation via computer simulations and/or
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questions within the theoretical and fundamental aspects of Mathematics, Physics, and Computer Science and Engineering, from various points of view and different abstraction levels. The selected candidate