22 postdoc-in-automation-and-control Postdoctoral research jobs in United Arab Emirates
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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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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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postdocs of the center. We also expect successful applicants to do cutting-edge interdisciplinary research and work in synergy towards improving the collaborations and connections among the different areas
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Description The Center for Artificial Intelligence and Robotics (CAIR) at New York University Abu Dhabi invites applicants to apply for the open Postdoc position in the Project Collaborative Multi
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algorithmic perspectives on large language models Statistical learning theory and complexity analysis Automated theorem proving and formal methods Random matrix theory and its applications in modern AI systems
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language models Statistical learning theory and complexity analysis Automated theorem proving and formal methods Random matrix theory and its applications in modern AI systems This position can be filled
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perspectives on large language models Statistical learning theory and complexity analysis Automated theorem proving and formal methods Random matrix theory and its applications in modern AI systems This position
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background. The Physics group at NYUAD currently has 15 faculty members and 20 postdocs and research associates; most are members of the Center for Astrophysics and Space Science (CASS). The group shares links
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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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imaging) at the exclusion of combining information across modalities. Our long-term objective is to develop a “phenotypic fingerprint” from multimodal imaging data in healthy controls to be used as an early