New Members & Collaborators

Fully funded PhD studentship in Physical AI for the Built World

Joint supervision by academics and researchers at CIRI and the University of Cambridge
Application deadline: 30 November 2026

Applications are invited for a fully funded PhD studentship investigating how artificial intelligence can understand, model and interact with the physical world, with a focus on infrastructure and construction.

This is a distinctive opportunity to develop your research through joint supervision by academics and researchers at CIRI – the Ward & Burke Centre for Infrastructure Research & Innovation, hosted at the University of Galway, and the University of Cambridge. You will be based at CIRI in Galway and will be expected to spend a visiting period of at least 6 months at Cambridge as part of your PhD.

The studentship is funded by the School of Engineering at the University of Galway.

The research opportunity

Infrastructure presents fundamental challenges for artificial intelligence. Developing reliable AI for these challenges requires methods that connect learning with physical understanding. Our research combines first-principles physics with machine learning, computer vision, sensing and simulation. We seek to develop methods that advance AI while addressing challenges in the delivery, inspection and maintenance of primary infrastructure.

We welcome proposals that connect methodological advances with a clear scientific or engineering question. Potential research directions include:

• Subsurface 3D reconstruction using physics-supervised machine learning and multimodal sensing. Develop methods to infer underground geometry and properties from complementary measurements, using physical models to guide learning and reconstruction.
• Digital twins – above and below ground. Explore how sensing, simulation and machine learning can support digital representations of the built environment that evolve as new observations become available.
• Physics-informed machine learning for generalisable particle contact and interactions. Develop learning methods that capture physical interactions and generalise across materials, geometries or loading conditions.
• Generalisable AI for construction robotics and autonomous systems. Explore how perception, learning and physical reasoning can help autonomous systems operate across changing construction environments and tasks.
• Scientific machine learning for primary infrastructure systems. Develop methods that combine physical models and data to improve the prediction and understanding of infrastructure behaviour.

These themes provide starting points for a research proposal. Applicants are encouraged to explain the questions they would like to pursue and how their ideas connect with the group’s research.

Supervision and research environment

Your primary supervisor will be Professor Brian Sheil. Your potential CIRI/Cambridge co-supervisors include A/Prof. Guangming Wang, Dr Olaf Wysocki, Dr Yixiong Jing and the wider team. The joint supervision brings together expertise in infrastructure engineering, machine learning, computer vision, robotics and digital twins. It offers an opportunity to develop research at the intersection of these fields and engage with researchers at both institutions. Your primary research base will be CIRI at the University of Galway.

Who should apply?

We welcome applications from motivated candidates with backgrounds in engineering, computer science, applied mathematics, physics or related disciplines.

The opportunity will particularly suit applicants who are interested in developing new AI methods grounded in physical systems. Relevant strengths may include:

• A strong foundation in mathematical or computational methods.
• Experience with programming, machine learning, numerical modelling, computer vision, robotics or sensing.
• The ability to formulate research questions and investigate them critically.
• A willingness to work across disciplinary boundaries and collaborate with researchers at both institutions.
• Publications at top computer vision / robotics / AI venues (e.g., NeurIPS, CVPR, ECCV, ICRA) is a plus

Your proposal should demonstrate a clear research interest and its connection to the advertised themes. We welcome applicants whose strengths come from different combinations of computational and engineering experience.

How to apply

Please email the following documents to brian.b.sheil@universityofgalway.ie:

1. Your CV, outlining your education, relevant experience and research or technical projects.
2. A one-page research proposal, describing the question you would like to investigate, why it matters, your proposed approach and its connection to the research themes above.

Use the exact email subject line: SoE_studentship_26

Application deadline: 30 November 2026

For informal enquiries about the opportunity or the fit of your research interests, please contact Professor Brian Sheil at brian.b.sheil@universityofgalway.ie.

We welcome applications from candidates with diverse backgrounds and experiences.