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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
, leveraging on data analytics and machine learning to improve learning outcomes and engagement in the classroom, and Development of personal GPT-powered AI tutors that use the knowledge from (1) to provide
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(SHORES) and the Division of Engineering, New York University Abu Dhabi, seek to recruit a Postdoctoral Associate to work on a fascinating project focused on the development machine-learning powered digital
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Associate Research Scientist / Post-Doctoral Associate in the Division of Science (Computer Science)
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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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
join forces to push the boundaries of data‑driven discovery. Our mission is two‑fold: to advance fundamental theory in probability and machine learning, and to translate those breakthroughs into high
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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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Description The Robot Learning & Control Lab (REAL Lab) at NYU Abu Dhabi is seeking an outstanding Post-Doctoral Associate to contribute to cutting-edge research in robot intelligence, machine
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in communication theory, signal processing, machine learning, and optimization theory. Strong verbal and written skills in English. Excellent analytical and problem-solving skills, and capacity
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(SHORES) and the Division of Engineering, New York University Abu Dhabi, seek to recruit a Postdoctoral Associate to work on a fascinating project focused on the development machine-learning powered digital
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in IEEE Communications Society’s and IEEE Signal Processing Society’s journals and conferences. Strong background in communication theory, signal processing, machine learning, and optimization theory
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with expertise in the following four areas: (1) working with large-scale digital trace data; (2) building and running natural language processing and machine learning workflows; (3) experimental design