10 machine-learning-phd Postdoctoral positions at NEW YORK UNIVERSITY ABU DHABI in United Arab Emirates
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. The candidate should have a PhD in Computer Science or a closely related field. Relevant background and skills include: Strong foundation in one of the following areas: Machine Learning / Information Retrieval
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undergraduate student research or junior graduate students. A formal training, education, or certification in a secondary area (beyond the main PhD focus) such as machine learning, artificial intelligence
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and his team to research on deep reinforcement learning, with the goal of making fundamental contributions in new algorithms and publishing in top machine learning venues. The team aims to make progress
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-edge technology on society, using machine-learning in optimizing networks components such as congestion control, and/or innovative usage of generative AI (e.g., stableDiffusion) in Web. The successful
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expertise in these topics are highly encouraged: Quantum Machine Learning, Machine Learning on Quantum Computers, Quantum Circuits for Machine Learning, Quantum Circuits for Topological Data Analysis, Design
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Post-Doctoral Associate to work on state-of-art research on security and privacy. There is a position available for 3 topics (applicants need to select one): 1) Private machine learning inference, 2
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such as Neural network vulnerabilities and defenses, Anomaly detection, Adversarial machine learning, Computer vision, and Autonomous Robots is desired. The successful applicant will work on various
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and his team to research on deep reinforcement learning, with the goal of making fundamental contributions in new algorithms and publishing in top machine learning venues. The team aims to make progress
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University Abu Dhabi (NYUAD), seeks to recruit a motivated Post-Doctoral Associate to work on cutting-edge machine learning / artificial intelligence applications that utilize human signals (e.g. text, audio
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, retrieval calculations, interior convection, machine learning, or aeronomy. Astrophysical research at NYUAD spans a wide range of topics, including astroparticle studies, stellar and planetary physics