This fully funded PhD (open to any nationality), sponsored by the European Union Horizon Europe programme, offers an exciting opportunity to develop next-generation digital twins for offshore wind turbines. The research will combine physics-based modelling, artificial intelligence, structural health monitoring and real-time data integration to improve asset reliability and predictive maintenance. Working within an international consortium of leading universities and industrial partners, the successful candidate will contribute to cutting-edge research that supports the digital transformation and decarbonisation of the offshore renewable energy sector.
Offshore wind is a cornerstone of the global transition to net-zero energy. As wind farms become larger and move further offshore, ensuring their structural reliability while reducing maintenance costs has become a major engineering challenge. Digital twins, artificial intelligence and structural health monitoring are transforming the way offshore assets are monitored and maintained, enabling safer, smarter and more sustainable renewable energy systems. This project sits at the intersection of offshore engineering, digital engineering and AI
The PhD will develop physics-informed digital twins for offshore wind turbines by integrating real-time monitoring data, advanced physics modelling and AI-assisted data analytics. The research will investigate data integration, structural state reconstruction, fatigue assessment, remaining useful life prediction and predictive maintenance. Digital twin development and validation using laboratory experiments will be undertaken to improve the reliability and operational performance of offshore wind assets.
The project is hosted by Cranfield University, one of the UK’s leading universities for postgraduate engineering research. It is funded by the European Union Horizon Europe programme and forms part of a large international research programme, involving leading universities, research institutes and industrial partners across Europe. The successful candidate will work within a multidisciplinary team with access to state-of-the-art laboratories and international expertise.
The research will contribute to the development of next-generation digital twin technologies for offshore wind systems, enabling improved structural integrity assessment, predictive maintenance and lifecycle management. The outcomes are expected to reduce maintenance costs, improve operational reliability and support the wider deployment of offshore renewable energy, contributing to global decarbonisation and energy security.
The student will become part of a major Horizon Europe collaborative project and have opportunities to work with international academic and industrial partners across Europe. The project offers opportunities to publish in leading journals, travel opportunities such as presenting research at international conferences and participating in collaborative meetings, and to develop multidisciplinary expertise in offshore engineering, AI and digital twins, and to gain other experiences in an international flagship project. Access to Cranfield’s cutting-edge specialist laboratories and research facilities will support both computational and experimental research.
The student will develop advanced skills in digital twins, AI, physics modelling, structural health monitoring, data analytics and scientific programming, together with experience in laboratory testing, project management and international collaboration. These highly transferable skills will provide excellent career opportunities in academia, offshore renewable energy, digital engineering, consulting, and the wider energy and technology sectors.
At a glance
- Application deadline26 Aug 2026
- Award type(s)PhD
- Start date02 Nov 2026
- Duration of award3 year (full-time)
- EligibilityUK, Rest of world
- Reference numberCRAN-0099
Entry requirements
Applicants should have a first or second class UK honours degree or equivalent in a related discipline. This project would suit graduates in Mechanical Engineering, Civil Engineering, Ocean Engineering, Offshore Engineering, Renewable Energy, Structural Engineering, Electrical Engineering, Computer Science, Artificial Intelligence, Data Science, or other relevant STEM disciplines. Experience in one or more of offshore systems, advanced sensors, experiments, programming, data analysis or AI modelling would be advantageous but is not essential. Applicants should have strong analytical and problem-solving skills, together with an interest in digital twins, AI and offshore renewable energy, and the willingness to collaborate with other partners to contribute to a multidisciplinary EU project.
Funding
Sponsored by EU, this studentship will provide a bursary of up to £28,830 (tax free) plus fees* for three years.
To be eligible for this funding, applicants must be classified as a Home fee status student. Eligibility for Home fee status is determined with reference to UK Department for Education rules. As a guiding principle UK or Irish nationals who are ordinarily resident in either the UK or Republic of Ireland pay Home tuition fees. All other students (including those from the Channel Islands and Isle of Man) pay Overseas fees. Further advice can be found on the UK Council for International Student Affairs (UKCISA) website.
Diversity and Inclusion at Cranfield
We are committed to fostering equity, diversity, and inclusion in our CDT program, and warmly encourage applications from students of all backgrounds, including those from underrepresented groups. We particularly welcome students with disabilities, neurodiverse individuals, and those who identify with diverse ethnicities, genders, sexual orientations, cultures, and socioeconomic statuses. Cranfield strives to provide an accessible and inclusive environment to enable all doctoral candidates to thrive and achieve their full potential.
At Cranfield, we value our diverse staff and student community and maintain a culture where everyone can work and study together harmoniously with dignity and respect. This is reflected in our University values of ambition, impact, respect and community. We welcome students and staff from all backgrounds from over 100 countries and support our staff and students to realise their full potential, from academic achievement to mental and physical wellbeing.
We are committed to progressing the diversity and inclusion agenda, for example; gender diversity in Science, Technology, Engineering and Mathematics (STEM) through our Athena SWAN Bronze award and action plan, we are members of the Women’s Engineering Society (WES) and Working Families, and sponsors of International Women in Engineering Day. We are also Disability Confident Level 1 Employers and members of the Business Disability Forum and Stonewall University Champions Programme.
Cranfield Doctoral Network
Research students at Cranfield benefit from being part of a dynamic, focused and professional study environment and all become valued members of the Cranfield Doctoral Network. This Network brings together both research students and staff, providing a platform for our researchers to share ideas, identify opportunities for collaboration and create smaller communities of practice. It aims to encourage an effective and vibrant research culture, founded upon the diversity of activities and knowledge.
Doctoral Researchers’ Core Development (DRCD) Programme
An important part of the research journey is developing key skills that will benefit a research students research and professional development. As a research student at Cranfield, you will be expected to attend the DRCD programme which comprises of four 1 week units which cover the key stages of your research journey. Workshops are held face to face, providing the opportunity for you to network and collaborate with your peers during these valuable development sessions. For further details visit Cranfield's Doctoral Network.
How to apply
For further information please contact:
Name: Dr Luofeng Huang
Email: luofeng.huang@cranfield.ac.uk
Phone: +44 (0)1234 758302
This vacancy may be filled before the closing date so early application is strongly encouraged.
Note, your application will not be considered unless all relevant documents have been uploaded. For more information please visit Applying for a research degree.
