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the safety and robustness of human-robot interaction. The postdoc will work on projects focusing on one or more of the following: Learning-Based Control: Developing reinforcement learning, imitation learning
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Reality to elicit users’ preferences for innovative transport systems. Applicants with a background in behavioral analysis and mathematical modelling are encouraged to apply. Terms of employment include
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. The researcher is expected to have (i) strong machine learning skills to improve model performance and robustness, and (ii) exemplary passion and motivation to pursue multidisciplinary research at the intersection
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modeling and characterization for communication and sensing in emerging spectrum for 6G and beyond, with a focus on the FR3, THz and optical frequency bands. This research will be conducted under the joint
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molecules tailored for DNP-NMR applications, benefiting from NYUAD’s state-of-the-art research infrastructure for organic synthesis and molecular characterization. Key Responsibilities Candidate will be
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, the candidate will find many international experts and postdocs with whom to interact. Weekly seminars are in place across the various research areas represented at NYUAD. The successful applicant will also
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, Neuroscience, or a related field. A strong background in functional neuroimaging with experience in decoding and/or encoding models is required. Candidates with experience with recurrent neural networks will be
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methodology will involve the development of mathematical models for signal transmission and reception, derivation of fundamental performance limits, algorithmic-level system design, and performance evaluation
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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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, climate, and human health. Examples of current active projects include: Developing optimization models to analyze and mitigate fine particulate matter (PM2.5) exposure from various infrastructure systems