PhD Researcher – Multi‑Objective Optimization of Maintenance Strategies in Aviation

About the role

We are looking for a PhD researcher to join a cutting‑edge project at the intersection of Aviation 4.0, predictive maintenance and big‑data analytics. The candidate will develop artificial‑intelligence and multi‑objective optimisation methods to improve the reliability, performance and energy efficiency of aeronautical systems.

Key responsibilities

• Design and implement machine‑learning models that process heterogeneous and uncertain industrial data (sensor streams, maintenance logs, operational records).
• Formulate and solve multi‑objective optimisation problems that balance operational performance, cost and environmental impact.
• Validate algorithms on real‑world aviation datasets and assess their impact on maintenance planning and equipment lifespan.
• Publish research results in scientific conferences and journals.

Required profile

• Master’s degree (M2) or engineering degree in computer science, artificial intelligence, data science or a related field.
• Strong foundation in applied mathematics, statistics and optimisation.
• Interest in complex systems modelling and predictive maintenance.

Required skills

• Machine learning and deep learning techniques.
• Experience with AI frameworks such as PyTorch and TensorFlow.
• Knowledge of big‑data processing concepts.