18 machine-learning-phd Postdoctoral positions at NEW YORK UNIVERSITY ABU DHABI in engineering
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must hold a PhD degree or have submitted a PhD thesis. Responsibilities of the Position: Research Conduct world class research in systems security and privacy. Write research articles and publish work in
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distributed decision-making. Applicants must have a PhD in Electrical Engineering, Mechanical Engineering, Computer Engineering, Applied Mathematics, Mathematics, or a closely related discipline, and are within
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developing new machine learning methodologies that tackle unique computational problems in healthcare applications. We use large real-world complex datasets, including data extracted from electronic health
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Description The Clinical Artificial Intelligence Lab at NYU Abu Dhabi seeks to improve patient care by developing new machine learning methodologies that tackle unique computational problems in
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-Doctoral 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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Post-Doctoral Associate in the Division of Engineering (Mechanical Engineering) - Dr. Mohammed Daqaq
and experimental, in the broad field of nonlinear mechanics. Preference will be given to applicants with expertise in machine learning, wave propagation, metamaterials, and/or fluid–structure
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collaborators. Requirements: Applicants should have a PhD in Computer Engineering, Computer Science, or a related field. Extensive and sound knowledge of ML, AI, DNN, LLMs/VLMs, Multimodal LLMs, RAG, Agentic
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-doctoral 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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related discipline, with a focus on security, privacy, or applied machine learning, and with less than 5 years post receipt of PhD. Demonstrated research experience in at least one of the lab’s research
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the group's core research areas, and a proven ability to conduct independent, high-impact research. Experience in cybersecurity for cyber-physical systems, digital twins, BIM, AI and machine learning