Designing smart space structures for extreme environments: from nonlinear dynamics to resilient mechanisms

About the Project

Supervisory Team: Andrea Cammarano and Dr Cristiano Martinelli

This PhD will develop AI-based predictive and control methods for nonlinear, regolith-resilient mechanisms in collaboration with ESA, combining structural dynamics, compliant design, and topology optimisation to create lightweight, intelligent space structures for next-generation exploration.

Future space missions will rely on smart, lightweight structures capable of surviving extreme environments — from vibration and temperature swings to abrasive lunar dust and orbital debris. This PhD project will develop AI-augmented methods to predict, control, and enhance the performance of nonlinear mechanisms that enable such resilience in space applications. In collaboration with the European Space Agency (ESA), the research combines nonlinear dynamics, compliant mechanism design, and machine-learning-based prediction and control to create adaptive, efficient structures for the next generation of spacecraft and planetary systems.

You will investigate how data-driven tools can complement physics-based models to forecast complex dynamic responses, guide topology-optimised designs, and improve damping and stability under uncertain or changing conditions.

The scope of this project can be tailored to your background and interests, ranging from:

• structural design and topology optimisation
• nonlinear vibration and control systems
• orbital and dynamic interactions of moving components, to
• mechanical resilience and debris-impact modelling.

This flexibility ensures that you can pursue your preferred balance between analytical modelling, numerical simulation, and experimental validation.

You will have access to the University of Southampton’s state-of-the-art facilities for additive manufacturing, vibration testing, and computational analysis, and work alongside ESA engineers on real-world mission challenges.

You will receive advanced training in nonlinear dynamics, machine learning for engineering prediction, topology optimisation, and control of flexible systems. Hands-on experience will include numerical continuation, additive manufacturing, and vibration testing, with opportunities for collaboration and technical exchange with European Space Agency engineers.

Entry requirements

You must have a UK 2:1 honours degree or its international equivalent in one of the following aerospace, mechanical engineering, structural engineering, or related discipline.

Essential skills: strong background in dynamics, vibration, or control.

Desirable skills: experience in numerical modelling (MATLAB, Python, or COMSOL) and an interest in AI or machine-learning-based prediction methods.

Fees and funding

We offer a range of funding opportunities for both UK and international students. Horizon Europe fee waivers automatically cover the difference between overseas and UK fees for qualifying students. Competition-based Presidential Bursaries from the University cover the difference between overseas and UK fees for top-ranked applicants.

Competition-based studentships offered by our schools typically cover UK-level tuition fees and a stipend for living costs for top-ranked applicants.

Funding will be awarded on a rolling basis, so apply early for the best opportunity to be considered.

For more information, please visit our postgraduate research funding pages.

How to apply

Apply now

• programme type: research
• academic year: 2026/27
• if you will be full time or part time
• faculty: Engineering and Physical Sciences
• search for programme PhD Engineering & the Environment (7175)
• please add the name of the supervisor in section 2 of the application.

Applications should include:

• your CV (resumé)
• 2 academic references
• degree transcripts/ certificates to date
• English language qualification (if applicable)