[Full coverage of tuition fees and an annual tax-free stipend of £22,780 for Home, EU and International students.] This PhD studentship at Imperial College London focuses on developing real-time machine learning and optimisation systems to address extreme weather challenges in aeronautics. As climate change intensifies, atmospheric events such as turbulence, storms, and shifting jet streams increasingly threaten flight safety and efficiency, leading to fuel wastage, longer travel times, and greater environmental impact. The project aims to enable aircraft to reroute safely and efficiently in real time as weather conditions evolve, moving beyond conventional pre-flight planning. The research is structured into three main stages: First, the student will create a scalable, automated pipeline to collect and harmonise heterogeneous datasets from sources like OpenFlights, OpenSky Network, Aviation Weather Center, and ADS-B providers, integrating real-time flight trajectories, route networks, and high-resolution weather data. Second, machine learning models will be developed to analyse these integrated data streams, identifying early signs of weather-induced disruptions and forecasting hazards such as turbulence and storm activity using graph-based clustering, fuzzy machine learning, and reduced-order models. Third, the student will design adaptive algorithms within a bias-aware ensemble Kalman filter framework to dynamically propose alternative flight paths, maximising safety and fuel efficiency while minimising congestion and emissions. The final deliverable will be a user-friendly decision-support tool for real-time rerouting recommendations, directly supporting pilots and flight control operations. The project is supervised by Professor Luca Magri and offers full funding, including tuition and a generous stipend for Home, EU, and International students. The studentship lasts 3.5 years and is open to candidates with a strong computational background in engineering, physics, mathematics, or computer science, with a First class honours degree or equivalent. The research will contribute to sustainable aviation practices and climate-aware air traffic management, with models evolving through real-world updates. Imperial College London is committed to equality, diversity, and inclusion, and encourages applications from all backgrounds.