19 machine-learning-"https:"-"https:"-"https:"-"https:"-"UCL" Postdoctoral positions at Nature Careers in United States
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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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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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, biochemical, cell, and tissue biology method skills. Experience in using computational analysis (biostatistics, machine learning, data science, physics, or a related field). We value diversity and strongly
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of the following methodologies: optogenetics, calcium imaging, viral tracing, tissue clearing, murine behavioral phenotyping, machine-learning behavioral analysis Familiarity with programming languages
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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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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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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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, including CAR-T cell therapies. Qualifications: Applicants must hold an MD, PhD, or MD-PhD. A strong background in immunology, neuroscience, and/or cancer biology is essential. Prior experience with iPSCs
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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
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high-dimensional, dynamic, networked system, applying techniques from machine learning, causal inference, statistics, and algorithms. No prior biomedical training is required—just strong quantitative