This postdoctoral position at Ecole Normale Supérieure (ENS-PSL) in Paris is dedicated to advancing research in uncertain data management and provenance within the Valda team of the Computer Science Department. The research is part of the PR[AI]RIE Artificial Intelligence Cluster and involves collaboration between Inria, CNRS, and ENS-PSL. The successful candidate will work on the ProvSQL system, a PostgreSQL extension designed to support a wide range of provenance semiring formalisms and probabilistic query evaluation. ProvSQL's key features include computation of provenance for SQL queries, probability computation over probabilistic databases using techniques such as naïve enumeration, Monte Carlo sampling, and knowledge compilation, and integration with relational DBMSs. The postdoc will focus on improving system performance, extending capabilities (such as new semirings, aggregate/query types, incremental updates, and large-scale experiments), and exploring real-world applications of uncertain data and provenance. Responsibilities include designing and implementing new features for ProvSQL, developing algorithms and data structures for efficient provenance circuit construction and probability computation, conducting performance experiments and benchmarking, theoretical analysis of new features, contributing to research publications, and open-source code development. Collaboration with application domains such as data analytics and sensor data uncertainty may also be involved. Applicants must have a PhD in computer science, international research experience, a strong mathematical background, good programming skills, and excellent English language proficiency. The position is full-time for one year, starting February 1, 2026, and located at 45 rue d’Ulm, Paris. To apply, candidates should send a detailed academic CV to pierre.senellart@ens.psl.eu mentioning the position. More information about the Valda team and ProvSQL can be found at https://team.inria.fr/valda/.