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-edge machine learning, including Large Language Models (LLMs), to enhance decision-making and planning in robotic systems. Qualifications: Applicants must have a PhD in Robotics, Control Theory
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, and Simultaneous Localization and Mapping (SLAM) is desired. The position is open to PhDs with background in robotics, controls, AI, and/or computer vision. The candidate is expected to work in a highly
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Research / Post-Doctoral Associate in the Division of Science Computer Science, Dr. Djellel Difallah
machine learning. The successful applicant will participate in research involving human computation, knowledge discovery, machine learning, and data science. The position will provide the opportunity
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Postdoctoral Associate to work on a fascinating project focused on the development machine-learning powered digital twin system for the structural performance of civil engineering structures. The project is a
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must have a PhD in Robotics, Control Theory, Mechanical or Electrical Engineering, Applied Mathematics, or a closely related field, with a strong focus on robot control, machine learning, and
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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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Research / Post-Doctoral Associate in the Division of Science Computer Science, Dr. Djellel Difallah
. The candidate should have a PhD in Computer Science or a closely related field. Relevant background and skills include: Strong foundation in one of the following areas: Machine Learning / Information Retrieval
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, seeks to recruit a Postdoctoral fellow or research scientist to conduct research in the area of computational heat transfer and machine learning for radiative transfer in scattering media. The successful
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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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, statistical signal processing, optimization theory, machine learning and artificial intelligence. The candidate is expected to actively participate in experimental work focused on building datasets of channel