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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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involved in perceptual judgments and economic decisions. Projects may involve the accuracy of judgments about probability, value, or risk; learning to forecast or categorize; the role of imprecise perception
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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
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The Center for Thermal Spray Research to learn more about our department/research. ● Within the predetermined research scope and methodology, conduct research experiments in the field of thermal spray and
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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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100 languages. Together, NYU's campuses in New York, Abu Dhabi, and Shanghai form the backbone of a unique global university, giving faculty and students opportunities to experience varied learning
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the CARINA project which is funded through a Research Ireland Frontiers of the Future grant. CARINA stands for Combining Machine Learning with Forefront Astronomical Instrumentation to Probe Intermediate Mass
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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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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | 20 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