27 machine-learning "https:" "https:" "https:" Postdoctoral positions at Cornell University
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world and a suite of associated machine learning tools. The incumbent will be advised by Dr. Laurel Symes (CAPS, [email protected]). Depending on the research direction, collaboration and additional
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avenues of research rather than a required work plan. They may be pursued individually or in combination, and we welcome other creative and strategic approaches. Statistical or machine-learning approaches
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Freedom and Free Societies Postdoctoral Associate The Program on Freedom and Free Societies at Cornell University (https://freedomandfreesocieties.cornell.edu/ ) invites applications for a two-year
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and/or case-crossover analyses, and have a promising publication record. Expertise in one or more of the following areas: statistical analysis of large data sets, machine learning, data visualization
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. • Expertise in one or more of the following areas: statistical analysis of large data sets, machine learning, data visualization, and a high level of independence with a publication record to support these
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across learning sciences, computer science, machine learning, HCI and education research. Research Role Research themes for the NTO Postdoctoral Associate include, but are not limited to: Developing
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are especially excited to hear from candidates eager to invent new tools, wetlab approaches for circulating nucleic acids, interpretable machine learning for biomarker discovery, and methods we haven’t imagined
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Molecular Biology seeks a Postdoctoral Associate to join the research group of Professor Fenghua Hu. Details of Dr. Hu’s laboratory, ongoing research projects, and recent publications can be found at https
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crystal / thin film scattering measurements, exploiting developments in artificial intelligence and machine learning. We also invite candidates with interests in beamline automation and autonomy
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world-class, mission-driven programs. Staff at the Lab teach undergraduate courses, advise graduate students, collect and disseminate world-famous digital resources on biodiversity, and engage with