29 computer-processor-phd-"https:" Postdoctoral positions at Carnegie Mellon University
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well as a generous retirement savings program with employer contributions. Unlock your potential with tuition benefits , take well-deserved breaks with ample paid time off and observed holidays , and rest
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with public and private data sets (e.g., O*NET and Lightcast). A computer science background and the ability to build data pipelines are a plus, as well as fluency in modern AI tools. This position
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about to receive a PhD in computer science or a related discipline, and prior experience with the type of work of the position. Carnegie Mellon University is an equal opportunity employer. It does not
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curious to deliver work that matters, your journey starts here! The Civil and Environmental Engineering Department at Carnegie Mellon offers a unique interdisciplinary program that enables you to develop
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curious to deliver work that matters, your journey starts here! The Civil and Environmental Engineering Department at Carnegie Mellon offers a unique interdisciplinary program that enables you to develop
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: PhD in areas covering computational neuroscience (e.g., neuroscience, mathematics, cognitive science, computer science), or a related discipline required Preferred experience in computing, in dynamical
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at Carnegie Mellon University invites applications for a postdoctoral researcher to lead projects at the interface of computational chemistry, machine learning, reaction mechanism elucidation, and automated
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curious to deliver work that matters, your journey starts here! The Civil and Environmental Engineering Department at Carnegie Mellon offers a unique interdisciplinary program that enables you to develop
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. Qualifications: Preferred applicants will have, or be close to completing, a PhD in Chemical Engineering, Biomedical Engineering, Mechanical Engineering, or a related field. Strong candidates will have expertise
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De Graef’s group in the Materials Science and Engineering Department in the College of Engineering. The postdoc will make use of the experimental and computational tools in the Materials