221 machine-learning-"https:" "https:" "https:" "https:" positions at New York University
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such as incentives, bonuses, clinical compensation, or other items. NYU aims to be among the greenest urban campuses in the country and carbon neutral by 2040. Learn more at nyu.edu/nyugreen. NYU is an
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research applications for projects thematically connected to existing research projects and initiatives at NYUAD's divisions of Arts & Humanities and Social Sciences (see https://nyuad.nyu.edu/en
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options; and retirement benefits (all subject to terms established by NYU as described at https://www.nyu.edu/employees/benefit/full-time/professional-research-staff.html). NYU considers factors such as
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candidate will have a demonstrated background in fluid dynamics, quantum physics, and machine learning as exemplified by a strong publication record. Previous experience on applied and computational
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are encouraged to apply. Terms of employment include competitive salary and benefits. Research in the Sreenivasan Lab (http://nyuad.nyu.edu/sreenivasan-lab) focuses on the neurobiological mechanisms that constrain
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cutting-edge research in multiple of the following areas, therefore prior expertise in these topics are highly encouraged: Quantum Machine Learning (QML), Machine Learning on Quantum Computers, Security
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successful candidate is also expected to sustain an active research agenda—demonstrated through publications and extramural funding—teach in the program, advise and mentor graduate students, and contribute
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status, color, creed, disability, domestic violence victim status, ethnicity, familial status, gender and/or gender identity or expression, marital status, military status, national origin, parental status
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, learning, and research. The personnel of UDAR work university-wide as well as within individual schools and colleges of the University to discover, motivate, cultivate, solicit, and steward alumni, parents
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the best set of optimizations. The goal of this project is to add support for automatic code optimization in Tiramisu. In particular, we want to use machine learning/deep learning to achieve this. Currently