Center Updates Dissemination & Implementation Systems Science

Applications are open for the 4th annual SSSI Summer Training Institute

Photo of group of summer institute participants at the Missouri Botanical Garden
2022-07-25 -- The Brown School at Washington University in St. Louis hosted the 2022 Systems Science for Social Impact (SSSI) Summer Training Institute for five days, including a reception and self-guided tour of the Missouri Botanical Garden in St. Louis Wednesday, July 27, 2022. Photo by Sid Hastings/Washington University.

The 4th annual Systems Science for Social Impact (SSSI) Summer Training Institute will be held at the Brown School at Washington University in St. Louis, from July 31 – August 4, 2023. Applications are open.

At this 5-day Summer Training Institute, participants will get a hands-on introduction to systems science methods that enhance the social impact of health and social science research. Led by experienced systems science scholars, this in-depth training institute will feature five major systems science tracks: agent-based modeling, group model building, social network analysis, system dynamics, and systems thinking. Participants will review the major concepts of their chosen track, learn analytic best practices, and apply the methods to real-world data.

The workshops are designed for faculty, advanced graduate students, recent graduates, and professionals from public health, social work, and social sciences.

Each applicant will select one track and optionally a second or third alternate track. Participants will have ample opportunities to interact with participants, instructors, and outside experts across tracks. The application process is open, and we will accept candidates on a rolling basis through July 5, 2023.

The Summer Training Institute is designed for advanced graduate students, recent graduates, professionals, and faculty from social work, public health, and social sciences who are interested in learning how systems methods can be applied in their research. Attendees should be familiar with quantitative descriptive and analytical techniques commonly used in their discipline (e.g., data visualization, regression analyses). Some experience with statistical software or programming languages is preferred.

You can apply and read more on the Institute’s website.

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