卡迪夫大学PhD position in Autonomous technologies in structural health monitoring for sustainable lightweight structures申请条件要求-申请方
主办方
卡迪夫大学
PhD直招介绍
About the Project
Description of Project
Join our diverse and inclusive team to transform the future of aviation as part of the UK’s EPSRC Centre for Doctoral Training (CDT) in Net Zero Aviation.
This fully funded (including fees and a tax-free bursary of £25,183) PhD, working with the Airbus company Testia will focus on the scientific investigation and technological implementation of autonomous monitoring for lightweight composite structures, developing real-time acousto-ultrasonic monitoring (akin to ‘listening for damage’) to detect changes in structural responses and identify damage in operational structures. This will be achieved through a multi-faceted approach, comprising:
Physics-Driven Modelling: The development of an underlying model or digital twin that accurately reflects the behaviour of structural ultrasonic waveguides under varying operational and ambient conditions.
Machine Learning Integration: The extraction, synchronisation, and utilisation of structural acoustic fingerprints from damage events (e.g., tool drops, delamination, cracks), captured by an onboard sensory network. These data will be used to train and optimise machine learning algorithms, enhancing the classification and predictive capabilities for damage events.
Real-Time Damage Identification Toolbox: The creation of an advanced toolbox for real-time damage detection that identifies the location, type, and severity of damage. This system will combine data-driven insights from in-situ sensor data with model-informed, physics-based understandings of structural waveguides, providing quantified metrics of emerging damage alongside confidence estimates. The data will be collected with experiments involving ultrasonic sensors on the test structures.
This PhD project integrates physics-based characterisation of structural acoustic phenomena with hybrid passive-active acousto-ultrasonic monitoring data. Leveraging autonomous technologies and machine learning, the goal is to establish an IoT-enabled autonomous monitoring system for in-service structures, improving structural resilience, optimising maintenance strategies, significantly extending the service life of critical aviation infrastructure. and supporting the transformation of assets to net zero by enabling more efficient maintenance and reduced material waste. Collaborating with industrial partner Testia, an Airbus company, you will explore practical applications in the aviation sector.
Research Environment
Based in the School of Engineering at Cardiff University, following an initial nine months of cohort based training at Cranfield University you will join Cardiff’s Computational Mechanics and Engineering AI research group, a group at the forefront of physics-informed digital twins – integrating advanced computational mechanics with artificial intelligence and machine learning to revolutionize the way we understand and maintain structural infrastructure. We are dedicated to developing physics-informed digital twins that provide real-time insights into the performance and health of critical structures, ensuring safety and efficiency in civil engineering and aerospace applications.
You will benefit from access to excellent facilities including the Cardiff University Structural Performance (CUSP) laboratories where you will be able to fabricate composite panels, undertake vibration, modal analysis and acousto-ultrasonic experiments as well as high performance computing facilities.
The studentship is in collaboration with Testia – an Airbus company who will be closely involved in your supervision and host a three month secondment as part of your training.
Learning and Development Opportunities
While working on this exciting research project, you will be provided with:
· A fully funded 4 year full-time PhD - £25,183 tax-free stipend per year
· Cohort and individual modular training covering technical, research, professional and personal development.
· Minimum of 3 months fully funded industrial placement at Testia. The expectation is that students will have regular access and contact with the Testia team at Bremen throughout the duration of the project to support their work, in addition to the industrial placement.
· Industrial supervision/mentorship scheme.
· Access to approximately 40 industrial, government & research partners from the wider aviation sector as part of the Net Zero CDT programme.
· Access to world class research and education facilities at Cardiff University and partner organisations.
Graduates of the CDT in Net Zero Aviation will emerge with a unique interdisciplinary combination of technical and professional skills, a deep understanding of the broader aviation ecosystem, and a sustainability-driven mindset. This comprehensive experience ensures graduates are prepared to lead and accelerate the decarbonisation of aviation from diverse roles across industry, academia, government, and policy.
Deadline for applications
19th June 2026. We may however close this opportunity earlier if a suitable candidate is identified.
卡迪夫大学 PhD position in Autonomous technologies in structural health monitoring for sustainable lightweight structures项目有没有奖学金，是不是全奖Phd招生，下面我们一起看一下【大学名称】Phd的奖学金资助情况
项目资助情况
Funding Notes
Amount of Funding
A fully funded 4 year full-time PhD - £25,183 tax-free stipend per year
Eligibility
Full funding is currently available to Home and International applicants on a full time basis. There are a limited number of International spaces available due to the UKRI 30% cap.
卡迪夫大学Phd申请条件和要求都有哪些？PhD position in Autonomous technologies in structural health monitoring for sustainable lightweight structures项目是不是全奖？有没有奖学金？下面我们一起看一下卡迪夫大学申请Phd直招需要具备哪些条件和要求，以及托福、雅思语言成绩要到多少才能申请。
申请要求
Academic Criteria
Candidates should hold or expect to gain a first or upper second-class honours (or their equivalent) in Civil/Mechanical/Aerospace Engineering or Computer Science/Physics/Mathematics or a related subject, or a masters degree. Optional - Previous laboratory or field experience would be advantageous
Applications are invited from highly motivated individuals with a strong background and
• A passion for research and a desire to tackle complex problems in structures.
• Proficiency in programming and computational tools relevant to mechanics and/or AI.
• Excellent analytical and problem-solving skills.
• Willingness to apply for competitive graduate funding for PhD studies
Applicants whose first language is not English will be required to demonstrate proficiency in the English language (IELTS 6.5 or equivalent)
报名方式
招生人信息
Dr A Kundu, Dr C A Featherston
Professor Email:
kundua2@cardiff.ac.uk
featherstonca@cardiff.ac.uk
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