AI Methods is developing AI-enabled operational intelligence for aviation, combining flight trajectory, operational, meteorological and environmental data to understand how conditions affect flight operations, performance and environmental impact.

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We are seeking a PhD candidate to develop data-driven methods for reconstructing, monitoring and analysing aviation operations from heterogeneous operational datasets.The initial application will focus on assessing and monitoring aviation environmental impacts, including non-CO₂ climate effects and contrails.

The research will form part of an Industrial PhD between Applied Innovative Methods (AI Methods) and Universidad Carlos III de Madrid, and will sit at the intersection of aviation operations, data science, climate impact and decision-support systems.

What you will work on




The candidate will develop the data and analytical methods required to transform large volumes of aviation operational data into operational and environmental intelligence. The work is expected to include:

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- Processing and integrating large aviation datasets, includingaircraft trajectory, flight-plan, airspace, meteorological and other operational datasets.
- Reconstructing historical flight operations and operational events from heterogeneous data sources.
- Developing aviation performance and environmental KPIs at flight, airport, airspace and network level.
- Connecting aircraft trajectories with meteorological and atmospheric information to estimate environmental effects, initially including contrail and non-CO₂ climate impact.
- Developing methods for monitoring, reporting and verification (MRV) of aviation environmental impacts.
- Building scalable pipelines for historical analysis and near-real-time monitoring.
- Identifying patterns linking environmental conditions, operational decisions

📌 Especialista industrial (Leganés)
🏢 AI METHODS
📍 Leganés