Topic: machine-learning infrastructure

Four-month, full-time research fellowship developing machine-learning infrastructure and reinforcement-learning methods. Projects can address training performance, distributed systems, synthetic-data and environment pipelines, or model generalization. Fellows receive researcher mentorship, a weekly stipend and benefits. Applications are reviewed on a rolling basis for the next cohort, expected in January 2027. San Francisco workspace access and remote participation from the United States, United Kingdom or Canada are available. A subsequent permanent role is not guaranteed.

Build and operate shared machine-learning infrastructure for CERN experiments and researchers. The role connects high-performance computing, cloud technologies and AI platforms used in scientific work.