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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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research appointment beginning July 1, 2026. Candidates are required to have received a PhD or equivalent in Mathematics or related field by the start of their appointment, and they may have up to three
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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, reinforcement learning, probabilistic modeling, and language-guided autonomy. Core Responsibilities: Conduct independent and collaborative research aligned with the themes above Mentor PhD and MS students Lead
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in the United States. Preferred methodological skills include statistical analysis of survey and other large-n data, qualitative interviews, and/or text analysis and machine learning skills
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 days ago
solid academic background in polymer synthesis and electrochemistry. The candidates should be self-motivated to explore new areas of studies including AI related and machine learning fields, have evidence
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an excellent work ethic and background in molecular simulation and machine learning. Job responsibilities will include: Develop simulation algorithms and software to model challenging gas adsorption behavior in
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learning. Job responsibilities will include: Develop simulation algorithms and software to model challenging gas adsorption behavior in porous materials Develop novel machine learning model for predicting
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are in compliance with the necessary trainings (both at the lab and at the institutional level). Minimum Education and Experience: A PhD degree in Computer Science, Electrical/Computer Engineering, or a
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. Responsibilities may include: Designing and conducting studies on the clinical impact of GLP-1 and other metabolic therapies Developing and applying computer vision and machine learning techniques to analyze