PhD Studentship in Aeronautics: Real-time machine learning and optimisation for extreme weather (AE0073)

PhD Studentship in Aeronautics: Real-time machine learning and optimisation for extreme weather (AE0073)

Start Date: Between 1 August 2026 and 1 July 2027

Introduction: Climate change is transforming the skies. Increasingly frequent extreme atmospheric events, such as turbulence, convective storms, and shifting jet streams, threaten flight safety and operational efficiency. These disruptions force aircraft to divert, consume extra fuel, extend travel times, and produce more contrails, amplifying aviation’s environmental footprint. Traditional pre-flight planning methods can no longer keep pace with the speed and complexity of these evolving weather systems. From a scientific perspective, flight planning and optimisation consist of complex, dynamically interacting systems that will be modelled in this project using complexity theory.

This PhD project aims to enable aircraft to reroute safely and efficiently in real time as atmospheric conditions change. By integrating scientific machine learning, real-world datasets, and real-time optimisation, the research will develop adaptive tools to support on-the-fly decision-making with time series forecasting. Depending on the candidate’s background, there will be opportunities to design quantum machine learning algorithms for time-series forecasting of chaotic and complex systems. 

The outcome will be a user-friendly decision-support system capable of real-time forecasting of chaotic and complex behaviours. Beyond the PhD, this research will contribute to sustainable aviation by enabling continuous model updates from real-world data. 

Supervisors: Prof. Luca Magri

Duration: 3.5 years.

Funding: Full coverage of tuition fees and an annual tax-free stipend of £22,780 for Home, EU and International students.

Eligibility: Due to the competitive nature of these studentships, candidates will be expected to achieve/have achieved a First class honours MEng/MSci or higher degree (or international equivalent) in a Computational background: engineering, physics, maths, or computer science.

How to apply:

• Stage 1: Submit your 2-page curriculum vitae (CV), transcripts and a 300-word statement explaining your motivation for applying to this PhD Studentship to: Supervisor Review Form. Our supervisors will perform a comprehensive review to long-list candidates.

Deadline: 8 January 2026

• Stage 2: Supervisors will email further instructions and an application link to long-listed candidates, inviting them to make a formal application to the PhD Studentship.

Contact: For questions about the project: Prof. Luca Magri

For queries regarding the application process, email Lisa Kelly, PhD Administrator

Equality, Diversity and Inclusion: Imperial is committed to equality and valuing diversity. We are an Athena SWAN Silver Award winner, a Stonewall Diversity Champion, a Disability Confident Employer and are working in partnership with GIRES to promote respect for trans people.

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