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of climate change. The position is geared for a recent PhD graduate with interest in collaborating across disciplines, and expertise in remote sensing, spatial data analysis, machine learning and computer
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clinical utility of depression subtypes, called ‘biotypes’, using both theoretically informed and machine learning approaches to disaggregate the heterogeneity of depression based on functional neuroimaging
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the School's programs: Stanford MD, MS, MSPA, and PhD students; visiting MD students seeking clinical clerkships; postdoctoral scholars and medical fellows; and medical practitioners seeking further professional
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and methods. · General computer skills and ability to quickly learn and master computer programs. · Ability to work under deadlines with general guidance. · Excellent organizational skills and
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. General computer skills and ability to quickly learn and master computer programs such as REDCap, Microsoft Office. Ability to interpret, adapt, and apply guidelines and procedures. CERTIFICATIONS
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. General computer skills and ability to quickly learn and master computer programs, databases, and scientific applications. Strong analytical skills and excellent judgment. Ability to maintain detailed
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to learn and utilize relational clinical databases, data integration, and statistics. Strong written and oral English communication skills. Computer skills, including word processing and spreadsheet
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from the lab’s large number of existing datasets and new data acquired in longitudinal studies. Visualize these data, process neuroimaging data and implement machine learning algorithms and models
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patients or research subjects. Experience with basic statistics. Strong general computer skills and ability to quickly learn and master computer programs. Strong analytical skills. Good oral and written
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learn and master computer programs. Strong analytical skills and experience with computer spreadsheets and database software. Proficiency with Microsoft Office and Excel. Ability to work under deadlines