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PhD in AI for Structural Engineering University of Leeds in United Kingdom
Degree Level
PhD
Field of study
Computer Science
Funding
Full funding availableDeadline
Apr 30, 2027
Country
United Kingdom
University
University of Leeds

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About this position
PhD opportunity at the University of Leeds in AI for Structural Engineering, supervised by Professor David Connolly in the School of Civil Engineering.
This project sits at the intersection of civil engineering, computer science, machine learning, computer vision, digital twins, physics-informed neural networks (PINNs), and materials science. Research themes include generative design, structural optimization, predictive health monitoring, automated defect detection, real-time sensor integration, and AI-driven discovery of sustainable or self-healing construction materials.
The post is non-funded, so applicants should be self-funded or already have external funding secured. The page also notes that applicants should have identified a planned funder before contacting the supervisor. International applicants are welcome, and the project is open to all nationalities.
Typical entry requirements are a first-class or upper second-class honours degree, or equivalent, in an appropriate discipline; some cases may require a Masters degree. Suitable backgrounds include Structural Engineering, Civil Engineering, Computer Science, Data Science, Mathematics, Statistics, Physics, Mechanical Engineering, and Aerospace Engineering. English language requirement: IELTS 6.0 overall with at least 5.5 in each component, or equivalent, unless exempt.
Deadline: 30 April 2027. Start date: 1 October 2027. Apply via the University of Leeds research degree portal and state the project title plus Professor David Connolly as proposed supervisor.
Funding details
Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.
How to apply
Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.
More information can be found here
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