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Cranfield University

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Fully Funded PhD in Intelligent and Sustainable Offshore Wind Systems Cranfield University in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

Full funding available
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Country

United Kingdom

University

Cranfield University

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Keywords

Computer Science
Environmental Science
Mechanical Engineering
Electrical Engineering
Artificial Intelligence
Civil Engineering
Energy Engineering
Digital Twin Technology
Life Cycle Assessment
Offshore Engineering
Techno-economic Analysis

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About this position

PhD opportunity: Intelligent and sustainable offshore wind systems at Cranfield University, Faculty of Engineering and Applied Science.

This fully funded PhD project focuses on offshore wind systems, digital twins, artificial intelligence, predictive maintenance, life cycle assessment, techno-economic analysis, and sustainability assessment. The research aims to develop next-generation digital twin methodologies for sustainable offshore wind assets, improving reliability, long-term performance, and environmental and economic outcomes.

The project is hosted at Cranfield University in the United Kingdom and is sponsored by the European Union Horizon Europe programme. It is part of a large international consortium involving universities and industrial partners across Europe. The student will work on data integration, digital twin development, computational modelling, experimental validation, and intelligent maintenance strategies for offshore renewable energy systems.

Funding: bursary of up to £28,830 tax free plus fees for three years. The opportunity is open to Home and Overseas fee status students.

Eligibility: applicants should have a first or second class UK honours degree or equivalent in a related STEM discipline. Suitable backgrounds include Mechanical Engineering, Civil Engineering, Environmental Engineering, Sustainability, Energy Systems, Renewable Energy, Electrical Engineering, Computer Science, Artificial Intelligence, and Data Science. Experience in offshore systems, sustainability assessment, programming, data analysis, or AI modelling is helpful but not required.

How to apply: complete the online application form and upload all relevant documents. Early application is recommended because the vacancy may be filled before the closing date. For enquiries, contact Dr Luofeng Huang at [email protected].

Start date: 02 Nov 2026.

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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