Post-Doctoral Research Visit F/M Postdoc position F/M Foundations of resource-efficient large-scale learning

Research algorithmic and mathematical foundations for useful, resource-efficient and trustworthy learning from large data streams. Topics include sparse deep networks, robust learning, provable algorithms and random sketches for manifold or graph-based models. The Lyon appointment is for one year and one month from 1 December 2026, with possible renewal. Gross monthly pay is EUR 2,788; computing, experiments and research travel are supported.

A PhD in applied mathematics or a relevant signal-processing/computer-science field, strong mathematics and statistics, and programming skills. Sparse representations or statistical machine-learning experience is preferred. Restricted-area security authorisation may be required.