(c) Neil Holmes - offshorewind

DREAM: Data-driven Reliability-centred Evolutionary Asset Manager

About this project

The UK is leading the world in the deployment of offshore wind energy and Hull is at the centre of the industry, with the largest companies in the sector based in the region (Siemens Gamesa Renewable Energy and Ørsted). The University of Hull is working with these companies and other leading organisations to support the development of the industry through Aura.

The rapid development of the offshore wind (OSW) industry in UK waters has opened up many challenges and opportunities for research and innovation.

The rapid development of the offshore wind (OSW) industry in UK waters has opened up many challenges and opportunities for research and innovation. This is particularly true of Operations and Maintenance (O&M) where novel approaches are required, and where many innovation opportunities exist. O&M accounts for 20-30% of the lifetime cost of electricity generated from OSW and is a priority within the Industrial Strategy Green Paper and for funding agencies. To exploit these opportunities for research funding, the University of Hull has recently agreed with the Offshore Renewable Energy Catapult (OREC) to establish a joint Offshore Wind Operations and Maintenance Centre of Excellence (O&M CE) with the purpose of supporting innovation to help reduce the lifetime cost of electricity and promote the UK supply chain. The Centre of Excellence will develop a portfolio of activities ranging from early stage research to nearer market development based around a series of roadmaps developed in collaboration with the OSW industry. Through discussion with OREC, six areas of focus have been identified: Human free O&M, Human factors in O&M, Data driven O&M decision making, Offshore logistics, planning and risk, Lifetime asset management and Whole life supply chain modelling. The recently awarded PhD cluster of 4 scholarships will conduct early stage research addressing these six priority areas, which will feed a pipeline of innovation that ensures the long term sustainability of the Centre of Excellence.

The successful candidate will be based in the appropriate academic school but will benefit from opportunities to collaborate with AURA, the O&M CE, and both of the Energy and Environment and the Logistics Institutes.

DREAM: Data-driven Reliability-centred Evolutionary Asset Manager

This PhD focuses on off-shore wind farms and develops techniques for prediction of failures and the evolution of optimal global plans of wind farm maintenance. The objectives of this PhD are: firstly, to develop techniques for predicting the Remaining Useful Life (RUL) of assets through condition monitoring and data analytics; secondly, to exploit prognoses of RUL in order to continually produce and update, through automated reliability/cost analysis and bio-inspired optimisation, an evolving optimal global plan of wind farm maintenance. The PhD builds on our strong track record on data analytics, reliability engineering and bio-inspired AI and will be carried out in collaboration with EDF Energy R&D UK. 


Please refer to the Engineering and Computer Science Research pages for more information. For further details, please contact Prof. Yiannis Papadopoulos.

Next steps


To celebrate the University's research successes, the University of Hull is offering a full-time UK/EU PhD Scholarship or International Fees Bursary.

Entry requirements

Applicants should have a BSc, BEng or MSc in Computer Science and/or Electrical/Mechanical Engineering with a Software Engineering background.

Applicants should have at least a 2.1 undergraduate degree or Master’s degree in the disciplines noted above, together with relevant research experience.

How to apply

Applications for scholarship consideration at the University of Hull should be made through the Postgraduate Application system.

On the second page of your application, please select “Graduate Scholarship” as the type of scholarship you are applying for. 

Applicants are strongly encouraged to first identify and contact a potential supervisor.

Application deadline: Monday 19 February