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(CSS) group is widely recognized as a leading center of computational social science research, lying at the intersection of computer science, statistics, and the social sciences. We have been heavily focused recently on the intersection of AI-based tools and human cognition, decision-making, and productivity. Additionally, our main areas of interest are: innovating ways to make data, models, and algorithms easier for people to understand; using AI to improve education; improving polling and forecasting; advancing crowdsourcing methods; understanding the market (and impact) for news and advertising. Our approach is motivated by two longstanding difficulties for traditional social science: first, that simply gathering observational data on human activity is extremely difficult at scale and over time; and second, that running experiments to manipulate the conditions under which these measurements are made (e.g., randomly assigning large sets of interacting people to treatment and control groups) is even more challenging and often impossible.
In the first category, we exploit digital data that is generated by existing platforms (e.g., email, web browsers, search, social media) to generate novel insights into individual and collective human behavior. In the second category, we design novel experiments that allow for larger scale, longer time horizons, and greater complexity and realism than is possible in physical labs. Some of these experiments are laboratory style and make use of crowdsourced participants whereas others are field experiments.
Other Research Internships atcan be found on the labs’ listing of opportunities or in theMSR New EnglandMSR NYCcomprise approximately fifty full-time researchers and postdocs working in computational social science, economics and computation, FATE, machine learning and AI, computational biology, and sociotechnical systems. The labs are highly collaborative and interdisciplinary and are actively engaged with the local academic and tech communities.
Internships are able to start as early as January. It is advisable to list as early a start date as possible.
Other Requirements
Please explicitly list in your cover letter:
Your data analytic toolset (e.g., R, Python, etc.)
Your web development toolset (e.g., Javascript, React.js, D3.js, etc.)
A link to any online code repositories (e.g., Github, OSF, etc.)
A link to your research website/publications
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
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