Internship title: AI-Assisted Health Monitoring and Predictive Maintenance for Satellite Ground Station Assets

The internship provides a unique opportunity to investigate how modern AI and machine learning techniques can support the monitoring, maintenance and resilience of operational ground segment infrastructure. Recent developments within both academia and industry demonstrate a growing interest in applying predictive maintenance concepts to satellite communications infrastructure, antenna systems and operational support environments.

The trainee will have access to operational expertise, real engineering datasets and a ground stations operations environment that cannot typically be replicated within an academic setting. The project offers the opportunity to apply and extend knowledge acquired through university studies while gaining practical experience in satellite ground segment operations, AI technologies and engineering analytics.

The outcomes of the project may support future innovations aimed at increasing operational efficiency, service continuity and infrastructure resilience across the EUMETSAT ground segment.

Following an initial familiarisation period with EUMETSAT operational services, ground segment infrastructure and monitoring systems, the trainee will:

• Review EUMETSAT ground station infrastructure, operational monitoring systems and maintenance processes.
• Develop a proof-of-concept dashboard or prototype tool for monitoring asset health and maintenance trends.

• Evaluate the applicability of AI tools and capabilities available through EUMETSAT ML Framework (MLF) for selected predictive maintenance use cases.
• Analyse the operational benefits, limitations and implementation considerations of AI-assisted predictive maintenance within EUMETSAT operations.
• Prepare technical documentation, presentations and a final report summarising findings and recommendations.

• Have the ability to work effectively in English;
• Be computer literate;
• Be intrinsically motivated and curious about the internship subject;
• Be able to work independently and collaboratively;
• Have the ability to take the initiative in researching ideas;
• Have the ability to collect, collate, conceptualize and present information clearly.

Additional advantageous requirements:

• Knowledge of one or more modern programming languages (e.g. Python, Java, C++, Go);
• Strong knowledge of state-of-the-art Artificial Intelligence (AI) techniques (including Large Language Models (LLMs) and Agents), data analytics and statistical methods;
• Interest in, or basic understanding of, satellite ground station architectures and operational systems.