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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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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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). The work spans: Close collaboration with researchers in neuroscience, engineering, and ethics. Human-in-the-loop brain/muscle-machine experimentation focused on learning pedagogy for adaptive neural systems
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and machine learning with Prof. Jason M. Klusowski (https://klusowski.princeton.edu). The position is for one year with the possibility of reappointment based on satisfactory performance and
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related to learning engineering and AI in education, working with a team of postdoctoral researchers, PhD students, and Master’s/undergraduate researchers across multiple universities and organizations
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proposal development and preparation of high-quality publications in top computer security, privacy, embedded systems, sensing, and networking venues. ● Pursue research topics such as protecting
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clinical features using machine learning and foundational modeling approaches. This work supports disease modeling across chronic kidney disease, acute kidney injury, cancer, and neurological conditions. A
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patients requiring urgent or emergent intervention. The fellowship provides comprehensive training in data engineering, exploratory analysis, statistical modeling, machine learning, and artificial
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psychoactive substances, in seized drug products or clinical samples. The candidate will have the opportunity to work directly with experimentalists to validate predictions made by their machine-learning models
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original research on clandestine printing networks using computational tools Contribute to publications in both AI and humanities venues (machine learning conferences and book history journals) Contribute