223 data-"https:" "https:" "https:" "https:" "https:" research jobs at Princeton University
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protects the privacy of your personal data. Student privacy rights are governed by the Family Educational Rights and Privacy Act (“FERPA”), as described in Section 2.7 of Rights, Rules, Responsibilities
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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, extended reality (XR), and
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, and robotics. ARG's research interests include topics such as robot learning, human-robot interaction, Generative AI, computer vision, closed-loop control, extended reality (XR), and computational
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Requirements: * A brief, one-page description of project; we encourage a graphical abstract *Cover Letter * CV * Brief letter of support from Princeton faculty mentor (one page) Apply at https
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University guidelines. Applicants must submit a CV, contact information for three references, and a cover letter describing their areas of expertise and interest. References may be contacted for the candidates
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employee benefits are offered in accordance with Princeton University guidelines. Applicants must submit a CV, contact information for three references, and a cover letter describing their areas of expertise
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a related field, and should have or be approaching a PhD in a related discipline (Physics, EE, Chemistry, or Computer Science). Applications must be submitted online at https://puwebp.princeton.edu
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for each scholar. Candidates must submit a CV, list of publications, a statement of research interests, and the contact information for three referees. Finalists will be invited to give a research talk
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submit the below materials (in English) at https://puwebp.princeton.edu/AcadHire/position/38404. 1. Cover letter 2. Curriculum vitae 3. Statement of research interests (1,000 - 1,500 words) 4. A
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propulsion. Applied Materials and Electromanufacturing Advancing plasma processing science and electrified manufacturing technology. Using high performance computing, machine learning and advanced numerical