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motivated Neuroscience postdoctoral fellow. In addition to neuroscience research experience, having familiar with machine learning/AI/ big data processing will be an asset. A major part of this PDF
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partners to reduce CO2 emissions in steel production using machine learning. You can find more information here . You will work on a theoretical and an applied project on data-enhanced physical reduced order
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learning, transfer learning, foundation models, and self-supervised learning. Experience in dealing with large medical datasets (e.g., electronic health records data or medical images) Ability to use high
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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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. You have a background in machine learning for spatial data (e.g., random forest, neural networks) or are open acquiring these skills. You have experience with handling large geospatial datasets and
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learning. The post-holder will be familiar with the use of these techniques and experience of dataset construction and data mining will be essential. The successful applicant will have completed an MPhil/PhD
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understanding of artificial intelligence applications and methodologies, such as working knowledge of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI
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computer programming in R and Python *Formal training or experience applying quantitative and spatial methods to human-environment questions *Excellent academic writing and communication skills in English
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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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and implement computational techniques in processing neuroimaging including CT and MRI modalities. Demonstrated ability in big data analytics and machine learning techniques. Expert ability in