97 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" positions at Princeton University
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Language and Intelligence, the Princeton Center for Statistics and Machine Learning, and the greater STEM community. This position works closely with librarians and information specialists, guiding
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: 280363223 Position: Postdoctoral Research Associate Description: The Department of Electrical and Computer Engineering invites applications for postdoctoral, or more senior, research positions. The term
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education. Connections working at Princeton University More Jobs from This Employer https://main.hercjobs.org/jobs/21889608/updated-assistant-professor-of-electrical-and-computer-engineering Return to Search
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of design, computation, and robotics. ARG's research interests include topics such as robot learning, human-robot interaction, Generative AI, computer vision, closed-loop control, additive manufacturing
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and written communication skills. Proficiency with computer/technical use and willingness to learn new systems and technologies. Physical Endurance: Ability to lift 20-50 pounds occasionally (e.g
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at https://puwebp.princeton.edu/AcadHire/position/40281 and submit a current curriculum vitae, research statement, and a cover letter. Contact information for three references is required. To learn more
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across the broad areas of Statistics and their applications in machine learning. The ORFE department is part of the School of Engineering and Applied Science which is pursuing several initiatives in
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-Sigler Institute for Integrative Genomics and the Computer Science Department at Princeton University. We seek candidates with computational biology, bioinformatics, computer science, machine learning
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the position involves working with researchers and running research studies, this is not primarily a research position. The work is in person, and having a car is helpful as recruitment of participants involves
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interested in computational materials design and discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling redox-active solid-state materials