75 machine-learning "https:" "https:" "CMU Portugal Program FCT" Postdoctoral positions at Duke University
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, religion, sex (including pregnancy and pregnancy related conditions), sexual orientation or military status. Duke aspires to create a community built on collaboration, innovation, creativity, and belonging
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, race, religion, (including pregnancy and pregnancy related conditions), sexual orientation, or military status. Duke aspires to create a community built on collaboration, innovation, creativity, and
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expression, gender identity, genetic information, national origin, race, religion, (including pregnancy and pregnancy related conditions), sexual orientation, or military status. Duke aspires to create a
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and mathematical modeling, hierarchical statistical modeling, machine learning, remote sensing, geospatial statistics) • Demonstrated ability to conduct independent research and publish high-quality
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orientation or military status. Duke aspires to create a community built on collaboration, innovation, creativity, and belonging. Our collective success depends on the robust exchange of ideas—an exchange that
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and as part of a collaborative, interdisciplinary team. Commitment to publishing research and pursuing a career in academic or translational research. Experience with statistical modeling, machine
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identity, genetic information, national origin, race, religion, (including pregnancy and pregnancy related conditions), sexual orientation, or military status. Duke aspires to create a community built on
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, religion, sex (including pregnancy and pregnancy related conditions), sexual orientation or military status. Duke aspires to create a community built on collaboration, innovation, creativity, and belonging
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data, identifying structural errors in the dataset, and for maintaining a record of all steps from data extraction to dataset assembly · Fitting of machine learning models · Development of instrumental
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, including development of new computational tools for processing large-scale biospecimen data Creation of novel machine learning frameworks for automated scientific analysis and discovery Design and