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to improve the autonomy of Field Robotic systems by fusing control theoretic and machine intelligence approaches. Formal models are directly applied in real experimental facilities. We are seeking a Post
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Experience in machine-learning modeling for solid mechanics applications Experience in the development and coupling of numerical methods for solid mechanics modeling Post-Doctoral Associate Employment at NYUAD
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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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a research context. Proficiency in programming languages relevant to AI and robotics (e.g., Python, LabView, Matlab, C/C++). Demonstrated knowledge in data science and machine learning techniques