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outstanding candidates to apply for a postdoctoral research position in Geometric Deep Learning, with a strong emphasis on applications to biology and scientific discovery. This unique research collaboration
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to systematically understand cancer biology, identify diagnostic and prognostic biomarkers, and improve cancer therapy. Projects will involve the development of AI solutions, including machine learning, deep learning
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A postdoctoral associate position is available to study the molecular and circuit basis of sleep. We use sophisticated genetic approaches in Drosophila and mice to study the genes and circuitry
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research and excellent digital literacy Strong interest in historical data, machine learning, data visualization, or digital hermeneutics Strong communication skills in English and good knowledge of French
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SD-25157 RESEARCHER IN ATMOSPHERIC PLASMA TREATMENT OF METALLIC SURFACES FOR INDUSTRIAL APPLICATIONS
will support the implementation of robust, efficient surface modification solutions in industrial settings. The postdoctoral researcher will conduct research in the atmospheric plasma treatment
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Overview A Postdoctoral Research Associate position is available in the Lacy-Hulbert Laboratory in the Center for Systems Immunology at Benaroya Research Institute. Research in the laboratory
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Ph.D. or equivalent degree in mathematics, physics, computer science, bioinformatics, or a related field Experience in developing deep learning models Ideally, prior experience in analyzing biological
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-energy molecules such as water, carbon oxides or N2 into fuels, chemicals and materials provides a promising alternative to the worldwide energy and environmental challenges. The postdoctoral researcher
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(multiomics), CRISPR genome editing, deep learning, network modeling, confocal and two-photon live imaging. Please visit the Özel Lab Website for more information. Ideal candidates will be highly motivated and
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Python is required. Programming in C or C++ is a plus. Background in statistical genomics, longitudinal modeling, non-parametric statistics, machine learning and deep learning are preferred and encouraged