61 machine-learning "https:" "https:" "https:" "https:" "https:" uni jobs at Princeton University
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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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(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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: -A strong background in science and a bachelor's degree is required. -Math and computer proficiency, along with meticulous record keeping is required. -Must be highly motivated, a team player, able to
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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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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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of novel algorithms, machine learning for parsing biological data sets (genomics, proteomics, imaging, neuroscience), and related areas at the interface of computer/data science and the life sciences
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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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. 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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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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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