97 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" positions at Princeton University in United States
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(provisional, probationary, international, or temporary licenses are not accepted). Strong oral and written communication skills. Proficiency with computer use and willingness to learn new systems and
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areas: -developmental biology -experimental and/or theoretical biophysics -experimental and/or computational genomics -computer science, statistics, and/or machine learning with applications relevant
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. Qualifications High School diploma or equivalent. Candidate must be Customer Service oriented. Must possess physical security experience, past law enforcement, or a military background deemed equivalent to meet
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(faculty, students, staff) operating machines and tools for independent research or educational purposes: -Organize and deliver instructional classes for new users of the SEAS machine shop -Instruct users in
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, the development and implementation of novel algorithms, machine learning for parsing biological data sets (genomics, proteomics, imaging, neuroscience), and related areas at the interface of computer
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: 280940099 Lecturer D-26-ECE-00003 | Faculty | Electrical and Computer Engineering The Department of Electrical and Computer Engineering at Princeton University has an occasional curricular need for lecturers
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techniques; large data processing and high performance computing; advanced causal inference and statistics; computer vision and novel applications of machine learning. Advanced knowledge of R or Python is
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beyond ITER with advances in HTS materials, manufacturing, sensors and machine learning. High current density cables are required for the design of compact HTS magnets in a fusion pilot plant (FPP
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Computer Science, Electrical and Computer Engineering, Princeton Language and Intelligence, the Princeton Center for Statistics and Machine Learning, and the greater STEM community.This position works closely with
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a current curriculum vitae, research statement, and a cover letter. Contact information for three references is required. To learn more about AI at Princeton, please visit https://ai.princeton.edu