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Field
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practice-engaged research on how engineers learn, how engineering knowledge and identities are formed, how we assess and evaluate learning, and how educational systems can be designed and transformed
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, ventriculomegaly). Experience in machine learning statistical methods. Experience in the acquisition of infant neuroimaging data. Prior experience working with infants and children in a research setting. Enthusiasm
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
the nation for federal research expenditures as well as for federally funded social and behavioral sciences research and development. Here at Carolina, our highly skilled postdocs play a vital role in our
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 8 days ago
machine learning and/or biomedical image processing. The ACM Lab is developing software to support AI-driven techniques to rapidly diagnose, track, and treat neurodisorders. The ideal candidate will have a
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, Hepatology, and Nutrition Postdoc Appointment Term: Fixed term for one (1) year with opportunity for renewal Appointment Start Date: ASAP Group or Departmental Website: https://med.stanford.edu/ibd-celiac
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website: https://cruchagalab.wustl.edu/ . Research Projects: Plasma, CSF and Brain Proteomic analysis. Biomarker identification through the use of machine learning and AI approaches. Integration
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
the nation for federal research expenditures as well as for federally funded social and behavioral sciences research and development. Here at Carolina, our highly skilled postdocs play a vital role in our
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State University and work closely with I-CREWS researchers across the state. The position emphasizes developing, integrating, and applying modeling approaches-including machine learning (ML), hydrologic
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research on how engineers learn, how engineering knowledge and identities are formed, how we assess and evaluate learning, and how educational systems can be designed and transformed to support meaningful
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systems at various scales, for example using ab initio electronic structure methods like density-functional theory, developing interatomic potentials with various methodologies including machine learning