UW awarded NIH grant for training in advanced data analytics for behavioral and social sciences

The University of Washington’s , or CSDE, along with partners in the and the , is among eight awardees across the country selected to develop training programs in advanced data analytics for population health through the National Institutes of Health’s Office of Behavioral and Social Sciences Research.

This five-year, $1.8 million training program at the UW will fund 25 academic-year graduate fellowships, develop a new training curriculum and contribute to methodological advances in health research at the intersection of demography and data science.

The new training program will be led by , assistant professor of sociology, and will build on CSDE’s graduate certificate in demographic methods by integrating training in advanced statistics and computational methods.

The inaugural cohort will begin the program in October and is composed of graduate students Ian Kennedy, Neal Marquez and Crystal Yu, all in sociology; Emily Pollock in anthropology; and Aja Sutton in geography.

“Our faculty are at the forefront of research programs grounded in advanced data analytics,” said Robert Stacey, dean of the UW’s College of Arts and Sciences. “This grant recognizes the important interdisciplinary work happening across the UW, and particularly in the social sciences, to build this knowledge into much-needed education and training programs.”

, associate professor of sociology and statistics, and , professor of statistics and biostatistics, led the grant application with support from , director of the CSDE and a professor of international studies, public policy and sociology, along with faculty affiliated with CSDE, CSSS and the eScience Institute.

The NIH review praised UW’s plans. “The leadership team has well-established credentials, complementary expertise, and a strong track record and the proposed program builds on an existing program with demonstrable record of success,” noted reviewers. “The curriculum – which offers coursework in statistical methods, machine learning, coding, databases, data visualization and data ethics – is well-thought-out and will provide trainees with numerous immersive opportunities.”

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