392 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "University of St" "St" "St" uni jobs at Princeton University
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). Works with Electrical Project Engineer And/or Director to learn campus standards and ensure implementation of design standards via design & submittal reviews. Learns and utilizes NEC, UL, NETA, ANSI, and
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Create a Job Match for Similar Jobs About Princeton University Princeton University is a vibrant community of scholarship and learning that stands in the nation's service and in the service of all nations
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training to successfully complete Department investigations. Show positive leadership by encouraging others to learn and develop, giving clear and direct guidance and feedback on their performance. Encourage
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, and dispatching first responders. DPS receives 4,700+ emergency and 33,000+ non-emergency calls annually. There are nearly 2 million campus-wide radio transmissions annually and 98,500+ Computer-Aided
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(i.e. machine learning, neural nets, LLMs). Prepare results and design figures for reports and presentations. Manage and manipulate data using requested languages, including Python, R, MATLAB, and STATA
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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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independently. Proficiency with Microsoft Office (including Word, Excel, Access, and Powerpoint) and Google Products (Drive, Docs, Sheets, Forms), and a willingness to learn new technologies. Ability to work in
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-switching devices. R&D lab or prototype hardware development experience. Basic machining or fabrication skills are a plus. Knowledge, Skills and Abilities: Working knowledge of high-voltage power systems
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will be considered until the position is filled. Applicants must apply online at: https://puwebp.princeton.edu/AcadHire/position/40381 The work location for this position is in-person on campus
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advanced degree may be considered if they have significant (multiple years) hands-on experience with advanced microscopy applications. Applications are accepted online at https://puwebp.princeton.edu