The UC Berkeley Computational Social Science Training Program (CSSTP) trains predoctoral students representing a variety of degree programs and expertise areas in the social sciences, including demography, public health, public policy, social epidemiology, social welfare, and sociology.
Fellows participating in this program develop advanced computational and data science analytics skills to address urgent needs in biomedical, behavioral, social and clinical research. They are being trained to take advantage of recent advances in medical informatics, electronic health records, big data analytics, mobile/wearable technologies, social media and web-generated data, as well as geospatial and administrative data.
David Harding, professor of Sociology and Faculty Director of the Berkeley Social Science Data Laboratory (D-Lab); Maya Petersen, MD, PhD, co-chair of the Graduate Group in Biostatistics and associate professor of Epidemiology and Biostatistics in the Berkeley School of Public Health; and Tim Thomas, BIDS Research Training Lead for the Computational Social Science Training Program, and Research Director of Berkeley’s Urban Displacement Project; currently lead this program, which was launched in spring 2020 with a five-year, $1.2 million grant from the National Institutes of Health (NIH) Office of Behavioral and Social Sciences (OBSSR) and its partner institute, the Eunice Kennedy Shriver National Institute of Child Health and Human Development.
View this program's event videos in the CSS Training Program video archive.
Berkeley Computational Social Science Training Program: Call for Fellowship Nominations — Faculty Submissions due April 29, 2021
March 17, 2021 | BIDS News
BIDS and D-Lab launch the Computational Social Science Forum
September 3, 2020 | Marsha Fenner | BIDS News
UC Berkeley announces new NIH-funded Computational Social Science Training Program
April 23, 2020 | BIDS News