16 phd-position-computer-science Postdoctoral positions at Carnegie Mellon University
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that cross disciplines. We approach scientific problems from fresh angles using creative interdisciplinary approaches while drawing on our strengths in the core social sciences. Tepper faculty members
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support the mission of the university through their work. Qualifications: PhD Degree in MSE/MECHE or a related field (e.g., physics, chemistry, chemical engineering) Publications in peer-reviewed journals
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, faculty members, researchers, and students are revolutionizing focus areas in advanced manufacturing, bioengineering, computational engineering, energy and the environment, product design, and robotics. In
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shares our values and who will support the mission of the university through their work. Qualifications: PhD in Materials Science and Engineering or a related field (e.g., physics, chemistry, chemical
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that cross disciplines. We approach scientific problems from fresh angles using creative interdisciplinary approaches while drawing on our strengths in the core social sciences. Tepper faculty members
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close to completing, a PhD in Chemical Engineering, Biomedical Engineering, Mechanical Engineering, or a related field Strong candidates will have expertise in one or more of the following areas
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close to completing, a PhD in Chemical Engineering, Biomedical Engineering, Mechanical Engineering, or a related field Strong candidates will have expertise in one or more of the following areas
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. We are looking for someone who shares our values and who will support the mission of the university through their work. Qualifications: PhD in Machine Learning, Computer Science, or a related field by
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. We are looking for someone who shares our values and who will support the mission of the university through their work. Qualifications: PhD in Machine Learning, Computer Science, or a related field by
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are highly desirable. For the quantitative position, the applicant must have a PhD in computer science, statistics, or related field. Experience with empirical studies of software artifacts and social network