AI-Driven Anomaly Detection in Atomic Clock Signals

07 ott - Italia
Italian Ministry of Education, University and Research

INRiM in Italy invites applications for a research fellowship focused on AI-based methodologies to monitor and analyse high-reliability space systems, with emphasis on atomic clock signals used in satellite navigation and timing infrastructures.
The work includes acquiring and validating datasets from ground-based and spaceborne clocks; developing data preprocessing procedures; and designing, training, and optimizing machine and deep learning algorithms for anomaly detection and
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