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emerging spectrum (FR3, MMW, sub-THz/THz) Extreme massive MIMO communications Analog, digital and hybrid beamforming architectures Reconfigurable intelligent surfaces Machine learning for wireless
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topics: Random matrix theory Free probability theory High-dimensional probability, concentration and functional inequalities Mathematical aspects of quantum information theory, machine learning and deep
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: Developing and implementing digital twin platforms and graphical user interfaces (GUIs) to support construction monitoring and decision-making. The role involves leveraging machine learning and data
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, controls, AI, and/or computer vision. The candidate is expected to work in a highly collaborative multi-disciplinary environment with other post-doctoral associates, PhD and undergraduate students, as
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MIMO communications Analog, digital and hybrid beamforming architectures Reconfigurable intelligent surfaces Machine learning for wireless communications Hardware-constrained signal processing
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inequalities Mathematical aspects of quantum information theory, machine learning and deep neural networks. While excellent candidates with other research interests might be considered, priority will be given
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language models, and machine learning. The position does not require teaching, but it may be possible to get teaching experience for compensation. You would join a group of over 20 post-doctoral fellows and
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Science, Computational Social Science, Computer Science, or Information Science. The position requires experience with at least one of the following: Data Science, Machine Learning, Computational Social
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at the intersection of control theory and machine intelligence. Methodologies of interest include: Robot modelling, Nonlinear and Optimal control, Reinforcement learning, and Data-driven modeling and control. The Post
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on cutting-edge machine learning / artificial intelligence applications that utilize human signals (e.g. text, audio, physiology). Technical Experience The successful applicant will have the following