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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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of PhD), or Research Associate (more than 3 years of PhD). A strong preference is for individuals with (a) computer science or computer engineering degrees with previous experience in natural
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Description The Division of Engineering at New York University Abu Dhabi seeks to recruit a motivated post-doctoral associate with a strong background in control systems and machine learning to join
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of substitution models using large dataset, successful applicants must then have a PhD and demonstrated experience in discrete choice models, machine learning techniques, big data, and optimization
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learning theory to join the research team of Prof. Muhammad Umar B. Niazi. The position focuses on the design and implementation of incentive mechanisms for sociotechnical and cyber-physical-human systems
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. Kyriakopoulos seeks 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. Marine
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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