14 machine-learning Postdoctoral positions at New York University in Ireland-University-Ranking-2024
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learning (ML). Our lab explores the intersection of artificial intelligence, and human-computer interaction, striving to create technologies that amplify human potential. The successful candidate will engage
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machine learning, Computer vision, Swarms, Autonomous Robots, hardware security, and Embedded systems development is desired. The successful applicant will work on various projects on robotics and computer
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associate will be conducting research on topics in machine learning and computational materials science.. In compliance with NYC’s Pay Transparency Act, the annual base salary range for this position is
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Difallah in the Division of Science, New York University Abu Dhabi, seeks a Post-Doctoral Associate or a Associate Research Scientist to join a lab focused on applied machine learning. The successful
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Researcher will work in Professor Benjamin Peherstorfer’s group (https://cims.nyu.edu/~pehersto/ ) on scientific machine learning at the Courant Institute of Mathematical Sciences where they will help
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). Experience with human-factors instrumentation and data streams: eye tracking, physiological sensors, and motion capture. Familiarity with data/video coding tools and computer vision (e.g., OpenCV, scikit-learn
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network inference and modeling, machine learning and deep learning. Experience in working with Arabidopsis and plant genome data is a strong plus. The position is expected to continue for multiple years
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. Responsibilities: Conduct research on automated reasoning and proof checker, AI-assisted collaboration. Develop and analyze algorithms for learning and optimization. Participate in collaborative research projects
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, disability, domestic violence victim status, ethnicity, familial status, gender and/or gender identity or expression, marital status, military status, national origin, parental status, partnership status
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, military status, national origin, parental status, partnership status, predisposing genetic characteristics, pregnancy, race, religion, reproductive health decision making, sex, sexual orientation