Research Assistant or Associate in Aircraft Multidisciplinary Design Optimisation

manufacturing constraints for early-stage design. You will get the opportunity to travel to international scientific conferences and to industry partners (Airbus).

Your work will focus on development methods for aircraft design in dynamic environments. Computational strategies for aircraft design optimisation are currently based on static (or static equivalent) conditions, but this can be too conservative for high-aspect-ratio wings under dynamic conditions, such as flight through atmospheric turbulence. This project will develop algorithms to bring dynamic aeroelasticity into the optimization loop on a framework that scales to industrial-level analysis. We will use high-performance numerical computing on modern hardware, thus leveraging the vast computational infrastructure built for AI to redefine the art of the possible in next-generation aircraft design.

What you would be doing:

You will develop computational methods for wing optimization that consider the nonlinear dynamic aeroelastic behaviour of the wings under a vast numbers of scenarios and identifies critical conditions and their changes with respect to wing design parameters. This will be achieved through GPU-accelerated computing, programme-level algorithm differentiation, and advanced software methods for collective operations over large parameter spaces. Outcomes will be embedded in an optimization framework that also includes structural sizing and failure analysis of wing components.

What we are looking for:

Research Associate:

Hold a PhD in Aerospace, Mechanical Engineering or a closely related discipline, or equivalent research, industrial or commercial experience

*Candidates who have not yet been officially awarded their PhD will be appointed as Research Assistant.

Research Associate and Assistant:

A recognised first class masters degree (or equivalent) in Aerospace, Mechanical Engineering or a closely related discipline

• Experience in computational modelling and design optimization, preferably in an aircraft design context
• Experience in scientific computing, in particular, using Python and JAX.
• Some experience with machine learning algorithms and GPUs
• An interest in working in a larger group, collaborating with industry.

What we can offer you:

• The opportunity to build a strong network with contacts at Airbus
• The opportunity to develop computational tools for early-stage aircraft wing design that will inform design practice at Airbus
• Ample scope for travelling to international conferences to disseminate the work done.
• Ample scope for publishing in leading journals.
• The opportunity to gain experience with cutting-edge computational methods at the interface of aeroelasticity, structural analysis & optimisation.
• The opportunity to gain supervision and project management experience.
• The opportunity to continue your career at a world-leading institution and be part of our mission to continue science for humanity.
• Grow your career: Gain access to Imperial’s sector-leading dedicated career support for researchers as well as opportunities for promotion & progression
• Sector-leading salary and remuneration package (including 39 days off a year and generous pension schemes).

Further Information

This post is available until 31st October 2029.

If you require any further details on the role please contact: Silvestre Pinho – silvestre.pinho@imperial.ac.uk

If you encounter any technical issues while applying online, please don't hesitate to email us at support.jobs@imperial.ac.uk.

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£45,399 to £59,484 per annum