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Postdoctoral Research Scholar in Machine Learning and Computational Genomics Department of Epidemiology, School of Public Health, University of Pittsburgh The Department of Epidemiology
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think outside the box, to learn fast, collaborate effectively, iterate quickly, and work at the interface of both experimental and computational design. Qualifications for Computer Scientists, AI/ML: PhD
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that currently lack effective treatments, such as Parkinsons Disease. By combining machine learning with quantum chemistry and structure based approaches, the project will accelerate the translation
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We are seeking a highly motivated and skilled individual to join our neuroimaging laboratory, which specializes in multimodal image fusion, multiparametric modeling, and machine learning techniques
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opportunity to contribute to cutting-edge research at the intersection of artificial intelligence, machine learning, and healthcare. The successful candidate will develop and apply advanced machine learning
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and exciting research opportunities for scientific inquiry. Overall, the distinct areas of investigation for the Grant and the Sengupta labs allows the ideal candidate to acquire and develop different
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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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highly interdisciplinary, integrating big data analysis, state-of-the-art machine learning models, mathematical modeling, and systems biology to elucidate the mechanisms of drug interactions in complex
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are leaders in such disciplines as genome-editing, AI/machine learning, protein engineering, cryo-EM/ET, NMR, single-molecule experiments and more. You will also collaborate with the wider community at St. Jude
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machine learning methods. The successful candidate will lead an independent research project dedicated to identifying abnormal behavior and neuronal activities in circuits of murine models of 22q11.2 and