68 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions in United Arab Emirates
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collaborators. Qualifications Applicants must hold a PhD degree in electrical/electronics engineering, telecommunications or related field. Other requirements include Expertise in several areas among
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Engineering, Computer Science, Applied Mathematics, or related fields Strong background in control systems, machine learning, and scientific computing Programming proficiency and experience with simulation
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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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Postdoctoral Associate to advance cutting-edge research in machine learning (ML). Our lab explores the intersection of artificial intelligence, and human-computer interaction, striving to create technologies
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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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inequalities Markov processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic
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. Contribute to mentorship of students and lab group discussions. Minimum Qualifications: PhD in Chemical Engineering, Environmental Engineering, Materials Science, Mechanical Engineering, or a related field
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Description As part of the Electrical Engineering program of the Engineering Division and the Center of Artificial Intelligence and Robotics at NYU Abu Dhabi the group of Prof. Kostas J
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life-cycle assessment. The post-doctoral associate will be expected to lead research efforts and contribute to publications in reputable academic journals. Qualifications: A PhD in Civil and
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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