Phd Studentship: Techno-Economic Optimisation of Robotic Inspection for Circular Offshore Energy Assets

PhD Studentship available on the RAINZ CDT programme at The University of Manchester.

Project Overview

• Project title: Techno-economic optimisation of robotic inspection for circular offshore energy assets
• Supervisors: Prof Maria Sharmina & Dr Pawel Ladosz
• Cohort research challenge: Long-term autonomous monitoring and maintenance of assets
• Year 1 MSc Course: MSc Renewable Energy and Clean Technology
• Year 2 – 4 PhD Location: The University of Manchester

Abstract: Offshore wind and marine energy assets operate in harsh, inaccessible environments where manual inspection is costly, hazardous, and infrequent. This inspection deficit means end-of-life decisions rely on conservative design lifetimes rather than actual asset condition, resulting in premature decommissioning, lost operational value, and suboptimal material recovery, undermining circular economy objectives critical to sustainable net zero pathways. This PhD project will integrate robotic inspection technologies with techno-economic modelling to enable condition-based circular economy decision-making for offshore energy infrastructure. The project will: (1) evaluate autonomous inspection platforms, e.g. aerial drones, climbing robots, and remotely operated underwater vehicles, for capturing degradation data across turbine blades, towers, foundations, and subsea cables; (2) develop a machine learning approach to translating multi-modal inspection data into remaining useful life predictions; and (3) create a dynamic techno-economic model linking real-time condition assessments to optimal intervention strategies (repair, refurbishment, remanufacture, or recycling) under different energy system scenarios. The model will use industry case studies, quantifying how robotics-enabled predictive maintenance affects lifecycle costs, critical mineral demand, and circular recovery infrastructure requirements.

About the RAINZ CDT

The EPSRC Centre for Doctoral Training in Robotics and Artificial Intelligence for Net Zero is a partnership between three of the UK’s leading universities (The University of Manchester, University of Glasgow and University of Oxford).

Robotics and Autonomous Systems (RAS) is an essential enabling technology for the Net Zero transition in the UK’s energy sector. However, significant technological and cultural barriers are limiting its effectiveness. Overcoming these barriers is a key target of this CDT.  The CDT’s research projects will focus on how RAS can be used for the inspection, maintenance and repair of new infrastructure in renewables (wind, solar, geothermal, tidal, hydrogen) and nuclear (fission and fusion), and to support the decarbonization of existing maintenance and decommissioning of assets.

Funding:

This 4-year studentship covers tuition fees at Home student rate, a tax-free stipend, and a Research Training and Support Grant. As part of TechExpert, successful Home applicants receive an additional £10,000 annual stipend enhancement.

Funding for this RAINZ CDT studentship is provided by The University of Manchester.

Eligibility

Applicants should hold a First or strong Upper Second-class honours degree (2:1 with 65% average), or international equivalent, in Engineering, Computer Science, Physics, Mathematics, or a related discipline. Applicants should also demonstrate evidence of programming experience.

How to Apply

Applications should be submitted through the RAINZ CDT website, where further information about the CDT is also available.  Informal enquiries can be made by emailing rainz@manchester.ac.uk.

• Deadline: Friday 15 May 2026
• Start Date: Monday 21 September 2026

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