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Meta’s Central Applied Science team is seeking PhD-level research interns to work on statistical modeling, economics, experimentation, game theory, and GenAI modeling and evaluation. The interns will collaborate across product groups to apply rigorous research and engineering to strategic problems.
Internships run twelve to twenty-four weeks, with multiple start dates. The role focuses on developing robust models, evaluating experiments, and advancing methodological innovation to inform Meta’s
Central Applied Science (CAS) is a research and development team which takes on the strategic bets most critical to Meta that require a unique combination of research and engineering to succeed. We generate real-world impact through a combination of scientific rigor, methodological innovation and engineering.
Central Applied Science is interdisciplinary, with expertise in computer science, statistics, machine learning, economics, political science, operations research, marketing science and sociology, among many other fields. This diversity of perspectives enriches our research and expands the scope and scale of projects we can address. We deliver value through collaborative projects with other groups at Meta and with the academic community. In addition, we build and open-source technical products aligned with our areas of expertise.
The Central Applied Science team is looking for PhD research interns with expertise in statistical modeling, economics, experimentation, game theory, GenAI Modeling and Evaluation. The team works closely with various product groups throughout Meta, bringing expertise in anomaly detection, bayesian modeling, bias correction, model evaluation, synthetic population, behavioral modeling and pricing, and applying them for various applications. We solve critical problems that enable Meta to make robust and trustworthy strategic decisions and build products that best serve and protect their users.
Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year.