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nonprofits to use machine learning and data science to modernize the public sector. We are an interdisciplinary team of data scientists, social scientists, engineers, and lawyers who are passionate about
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University School of Medicine. We serve all populations of students and trainees who participate in the School's programs: Stanford MD, MS, MSPA, and PhD students; visiting MD students seeking clinical
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a particular focus in immunology, neuroscience, and/or computational science/machine learning. That said, we give high priority to the overall originality and promise of the candidate’s work, and
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in projects and operations to design, implement, and support innovative technical solutions. Areas could include machine learning algorithms, text and image processing techniques, API programming
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and early-onset cases without a known genetic cause. We are also interested in genetic interactions (epistasis), tandem repeats, machine learning, and other areas of AD research that have not yet been
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ability to quickly learn and master computer programs, databases, and scientific applications. Strong analytical skills and excellent judgment. Ability to maintain detailed records of experiments and
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): Comprehensive understanding of scientific principles. General computer skills and ability to quickly learn and master computer programs, databases, and scientific applications. Strong analytical skills and
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University School of Medicine. We serve all populations of students and trainees who participate in the School's programs: Stanford MD, MS, MSPA, and PhD students; visiting MD students seeking clinical
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pursuing equitable, accessible and effective learning for all. The Educational Opportunity Project (EOP), housed within the GSE, is dedicated to measuring educational opportunity in every community in
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, we're pursuing equitable, accessible and effective learning for all. The Educational Opportunity Project (EOP), housed within the GSE, is dedicated to measuring educational opportunity in every community