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enable physics-informed AI agents that accelerate discovery in catalysis science. The successful candidate will focus on the development and application of machine learning and AI approaches to analyze
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Investigator, Dr. Hwan Kim , in the department of Microbiology and Immunology. Please visit the Kim Laboratory to learn more about our department/research. The incumbent will conduct research and ensure
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Associate Research Scientist / Post-Doctoral Associate in the Division of Science (Computer Science)
machine learning. The successful applicant will participate in research involving human computation, knowledge discovery, machine learning, and data science. The position will provide the opportunity
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. The University’s unique applied learning pedagogy integrates work and study, embedding authentic learning experiences within real-world environments. Through strategic partnerships forged by our faculty with
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. Visit The Office of Postdoctoral Affairs to learn more about our postdoctoral community. Resume/CV and cover letter should be included with the online application. Stony Brook University is committed
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experience in computational and machine learning approaches for use in the quantitative measurement of human learning and its associated behaviors and motivational constructs. A strong applicant will hold Ph.D
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projects within the CUS related to urban sustainability, environmental monitoring, and urban resilience. Key Duties • Design and implement machine learning and deep learning models for hydrological
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | 26 days ago
data analysis methods to study biological memory circuits and their applications to machine learning. Building on recent work from the Fiete Lab, the role focuses on identifying principles of biological
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research achievements. The University’s unique applied learning pedagogy integrates work and study, embedding authentic learning experiences within real-world environments. Through strategic partnerships
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University’s distinctive applied learning pedagogy integrates work and study, embedding authentic learning experiences within real-world settings. Through strategic partnerships forged by our academic staff with