AI-Driven Anomaly Detection in Atomic Clock Signals

Italian Ministry of Education, University and Research; Italia; In loco; EUR 35.000 - 55.000; Tempo pieno

Descrizione del lavoro

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

Competenze

• Qualifications and interview.
• Please refer to the public selection notice published on the website indicated above for details regarding the admission requirements and the selection criteria.

Mansioni

• Develop AI-based methodologies for monitoring high-reliability space systems.
• Design, training and optimisation of ML algorithms for anomaly detection and characterisation.
• Dissemination of results through technical reports and scientific publications.

Descrizione del lavoro

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