Artificial Intelligence and Data Science for Public Policy

The School of International and Public Affairs at Columbia University in the City of New York invites applications from scholars working in the field of Artificial Intelligence and Data Science for Policy. Candidates should have deep expertise in AI/ML/data science methods and the drive to see applications through to real world impact in public policy settings. Questions of interest could include, for example: the regulatory, political, or economic questions arising from increasing reliance on AI in the public and/or private sectors; the social and political consequences of reliance on algorithmic approaches to public policy implementation; methodological development at the intersection of social science and AI/machine learning. It is advantageous to have expertise in at least one applied domain, which could relate to SIPA’s global policy challenges: democratic resilience; technology and innovation; geopolitical stability; inclusive prosperity and macroeconomic performance; climate and sustainable development.

In addition, this search has the following priorities:

• A research agenda that bridges a public policy domain and a technical area of AI, machine learning, data science, or related computational methods
• A desire to have real-world impact through both technical innovation and its application to practical problems
• Experience teaching computational or numerical skills in public policy-related domains
• Interest in contributing to cross-sector collaborations that connect academia with government, industry, and communities, with the aim of informing evidence-based policy around AI

The successful candidate will contribute to teaching and intellectual leadership in the SIPA Data Science for Policy curriculum at the master’s and undergraduate levels.

This position is at the rank of Assistant Professor, tenure track, and will begin July 1, 2027, or as soon as possible thereafter.

Ph.D. in a field related to Artificial Intelligence and Data Science for Policy - including Data Science, Machine Learning, Computer Science, Political Science, Economics, Statistics, or another policy-related discipline - is required at the time of appointment. Candidates will be expected to sustain a strong commitment to research, publication, and teaching.