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. The position requires experience with at least one of the following: Data Science, Machine Learning, Computational Social Science, Big Data. Relevant skills could include statistical analysis, data management
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(e.g. Python, Julia), You have an interest in, or experience with, machine learning approaches for scientific data analysis. You have a strong interest in interdisciplinary research and enjoy
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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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platform for X-ray absorption spectroscopy by integrating LLMs, scientific machine learning, physics-aware workflows, and strong computational chemistry/electronic-structure expertise. The researcher will
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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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main PhD focus) such as additive manufacturing, advanced/hybrid manufacturing, machine learning, artificial intelligence, computer vision, robotics, UAVs, etc. is a plus. Other preferred qualifications
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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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National Energy Technology Laboratory (NETL) | Pittsburgh, Pennsylvania | United States | about 14 hours ago
lab results to predictive reservoir models. Through this project, the participant will learn about hands on lab experience, modeling, and presenting and publishing results. The participant will: (1
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must possess substantial experience in artificial intelligence and machine learning methods, specifically in AI-driven materials discovery, machine learning applications for materials, or generative AI
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affiliates reflect strengths in machine learning, biological modeling, data ethics, data sovereignty, computer science, environmental data science, climate change policy and modeling, evolutionary genetics