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of application a track record of successfully completing several quantitative methods or mixed method graduate courses a dissertation or published manuscript that relies on a quantitative or mixed-method approach
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) signaling. The Huttenhain lab integrates cutting-edge MS-based proteomics, functional genomics, imaging, and other molecular biology techniques to profile the spatiotemporal nature of GPCR signaling networks
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substantial component of the work focuses on large scale empirical research in international macroeconomics and finance. The Global Capital Allocation Project (GCAP) Lab mixes data, economic theory, and
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contribute to curating and publishing this dataset. Last but not least, the postdoctoral fellow will contribute their unique mix of expertise and interest in leveraging human-centered AI tools to improve
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, electrical engineering, experimental physics, or a related field Strong programming and signal processing skills, with experience in Python and/or MATLAB Demonstrated ability to work independently and
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research program related to the language, literacy, and culture of African Americans. They should have experience with mixed methods research in the humanistic social science tradition. As a portion of the
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immune responses; and the first studies to define how PCPS products are generated. Altogether, these innovations could result in the translation of point mutations in an intracellular protein into
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study of ECE and policy impacts. Strong data analytical skills using advanced statistical methods (such as mixed effect models, multilevel modeling, structural equation models, longitudinal modeling, etc
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@stanford.edu (link sends e-mail) The faculty point of contact for this fellowship is Wendy Gu: xwgu@stanford.edu (link sends e-mail) Application deadline is June 20, 2025. Applications will be reviewed on a
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in Neuroscience, Biomedical Engineering, Computational Biology, or a related field. Strong background in signal processing, including neuroimaging and/or electrophysiology (EEG, MEG) data analysis