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, faculty, and staff in Computer Science, Electrical and Computer Engineering, Princeton Language and Intelligence, the Princeton Center for Statistics and Machine Learning, and the greater STEM community
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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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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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. Responsibilities Application of Domain Expertise: Maintain strong command of AI and machine learning concepts, including underlying science, math, and algorithms; stay current through reading publications, reviewing
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limited to synthetic and chemical biology approaches to cellular computation and biomolecular logic design, the development and implementation of novel algorithms, machine learning for parsing biological
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learning to reconstruct perceived information from functional MRI in real time. For more information on Professor Norman’s lab, see https://compmem.princeton.edu. Questions should be directed to Professor
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. Fabricate parts as required using a variety of equipment and tools such as: milling machine, lathe, drill press, band saw, and other industrial tools. Assist in the set up and operation of pneumatic
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collected from these studies, subject recruitment, and some administrative work. Depending on qualifications/interest, the research specialist may also assist with developing computational models of learning
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. Willingness to work in collaboration with consulting physicians. Flexibility and dependability. Excellent computer skills, ability to learn the UHS-specific program, Medicat. Be knowledgeable in principles and
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career at our national laboratory. The apprentice will receive pay and benefits, as well as all the RTI is fully paid for by PPPL. PPPL apprenticeship website: https://www.pppl.gov/work-with-us