PhD Studentship - DETECT - Development of Evaluation Tools for Effective Composite Testing

This 3.5-year PhD project is fully funded and open to home students. The successful candidate will receive a tax-free stipend set at the UKRI rate (£20,780 for 2025/26) and tuition fees will be paid. We expect the stipend to increase each year. The start date is October 2025.

We are seeking a highly motivated PhD candidate to join NDT lab for an exciting project focused on the advanced characterization of defects (e.g., porosity, wrinkles, voids, resin rich regions, blisters) in composite materials. These significantly affects the mechanical performance, durability, and safety of composite structures. Accurate detection and quantification are therefore essential for quality assurance and structural integrity assessment.

This project, supervised by Dr. Leandro Maio and Prof. Prasad Potluri, will combine state-of-the-art non-destructive evaluation (NDE) techniques, including ultrasound and thermography, with cutting-edge artificial intelligence (AI) to enhance the detection and estimation of defects in composites.

The successful candidate will:

• Investigate the formation, distribution, and impact of defects during composite manufacturing;
• Develop and refine ultrasonic and thermographic inspection methods for defect detection;
• Apply AI and machine learning techniques to process, analyze, and interpret complex NDE data;
• Create AI models for automated defect detection, classification, and quantification;
• Integrate multi-modal NDE data for robust defect characterization and decision support.

This research project addresses a critical need for reliable, efficient, and cost-effective non-destructive evaluation methods to detect and characterize common defects in composites. By developing advanced ultrasonic and thermographic techniques, and combining them with modern data processing, this work aims to improve manufacturing quality control, enhance structural safety and reliability, reduce maintenance costs, support certification and standards, enable automation and smart manufacturing.

Overall, this research will contribute directly to making composite manufacturing more sustainable, cost-efficient, and safe, providing industries with practical tools to meet growing demands for lightweight, high-performance structures.

Therefore, discover, innovate, join our leading research team!

2.1 BEng in Electronic Engineering/ MEng in Mechatronic Engineering, 2.1 BSc Physics or

2.1 BSc in Materials Science, MEng in Materials Science, 2.1BEng/MEng in Mechatronic Engineering, 2.1 BEng/MEng in Mechanical Engineering, 2.1 BSc in Physics, MPhys in Physics.

To apply, please contact the supervisors Dr Leandro Maio - leandro.maio@manchester.ac.uk and Dr Potluri - prasad.potluri@manchester.ac.uk. Please include details of your current level of study, academic background and any relevant experience and include a paragraph about your motivation to study this PhD project.

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