The Causal Learning and Reasoning (CLeaR) group in the Department of Philosophy at Carnegie Mellon University develops methods and platforms for learning causality, including hidden causal variables, from various types of observational data and makes use of causal principles to perform principled reasoning and decision-making. It invites applications for two one-year postdoctoral fellowships beginning October 2026, potentially renewable for a second year.
A Ph.D. in computer science, philosophy, statistics, or a closely related discipline is required. We seek strong researchers with demonstrated experience in causal learning or inference and an interest in supporting the group's mission.
Carnegie Mellon University is an equal opportunity employer. It does not discriminate in admission, employment, or administration of its programs or activities on the basis of race, color, national origin, sex, disability, age, sexual orientation, gender identity, pregnancy or related condition, family status, marital status, parental status, religion, ancestry, veteran status, or genetic information. Furthermore, Carnegie Mellon University does not discriminate and is required not to discriminate in violation of federal, state, or local laws or executive orders.
At the SEI, we research complex software engineering, cybersecurity, and AI engineering problems; create and test innovative technologies; and transition maturing solutions into practice. We have been working with the Department of Defense, government agencies, and private industry since 1984 to help meet mission goals and gain strategic advantage.
