87 parallel-and-distributed-computing-phd research jobs at Carnegie Mellon University
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to the department by providing support for an industry-sponsored project focused on optimizing distributed healthcare supply chains using AI and analytics. Core responsibilities include: Help build machine learning
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to healthier, cleaner, more efficient future for all. A research collaboration is being funded by the Energy and Environment Solutions (E2S) program of the Universite de Pau et des Pays de l’Adour (UPPA) and
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distribute information for meetings, conferences and publications and conduct occasional meetings with project sponsor personnel; Other duties as assigned Adaptability, excellence, and passion are vital
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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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Mohadeseh Taheri-Mousavi’s group. The postdoc will develop and conduct advanced machine learning techniques combined with computational research to study the mechanical behavior of welds. Responsibilities
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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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CMIST is a university-wide institute that integrates Carnegie Mellon’s leadership in computer science and engineering with its distinguished tradition of interdisciplinary research. Combining
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through their work. You should demonstrate: Strong analytical abilities Excellent organizational and planning skills Effective problem-solving and critical reasoning skills Qualifications: PhD in Economics
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through their work. You should demonstrate: Strong analytical abilities Excellent organizational and planning skills Effective problem-solving and critical reasoning skills Qualifications: PhD in Economics
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engineering, earth science, computer science, or related field required. A PhD specializing in glacier modeling, remote sensing, and/or statistics preferred. Python coding experience preferred. Strong