June 23rd to July 2nd, 2020 | ENSAE | Plateau de Saclay, France


ATTENTION: SICSS-Paris has been postponed until 2021 due to COVID-19.

From June 23rd to July 2nd, ENSAE will sponsor a Summer Institute in Computational Social Science, to be held in Paris (on the Plateau de Saclay campus). The purpose of the Summer Institute is to bring together graduate students, postdoctoral researchers, and beginning faculty interested in computational social science. The Summer Institute is for both social scientists (broadly conceived) and data scientists (broadly conceived).

The instructional program will involve lectures, group problem sets, and participant-led research projects. There will also be outside speakers who conduct computational social science research on a variety of topics. Topics will cover digital data collection and curation, text as data, website scraping, digital field experiments, mass collaboration, machine learning, and ethics.

There will be ample opportunities for students to discuss their ideas and research with the organizers, other participants, and visiting speakers. Because we are committed to open and reproducible research, all materials created by faculty and students for the Summer Institute will be released open source, mostly in French.

Participation is geared towards Ph.D. students, postdoctoral researchers, and early career stage faculty. Most participant costs during the workshop, including housing and most meals, will be covered. A travel allowance can be requested should the participant need it to attend. We welcome applicants from all backgrounds and fields of study, especially applicants from groups currently under-represented in computational social science. About 20 participants will be invited, and participants are expected to fully attend and participate in the entire program.

Application materials are due on March 20th, 2020.

Host a Location

You can host a partner location of the Summer Institutes of Computational Social Science (SICSS) at your university, company, NGO, or government agency.

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