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  Combination of sensor fusion and machine learning for subsea structure inspection

   Department of Naval Architecture, Ocean & Marine Engineering

   Applications accepted all year round  Funded PhD Project (Students Worldwide)

About the Project

Naval Architecture, Ocean & Marine Engineering (NAOME) department in the University of Strathclyde in collaboration with Ilosta Ltd. is offering a PhD/EngD position in a project: Combination of sensor fusion and machine learning for subsea structure inspection.

Ilosta Ltd. is an engineering company working on cutting edge technology for assessing the integrity of structural components. Via visual inspection, machine learning and in-house developed methods, we assess the structural safety of components in different industries, e.g., wind power, subsea, piping and pressure systems, nuclear, oil and gas, etc. 

As part of the work which Ilosta is carrying out in the subsea inspection field, the chosen candidate will work with Ilosta in the development of better understanding of structural risk assessment of subsea structures. Using Ilosta's technology and platform, the candidate will further research state-of-the-art technology for determining the structural integrity of subsea structures.

An essential skill required from the applicants is the ability to reliably develop, deploy and maintain machine learning pipelines in Python programming language. A desired candidate should also be comfortable in working with optical footage and be open to learn about more advanced optical techniques such mutli- and hyperspectral analysis. Knowledge of point-cloud processing (LiDAR data) would be highly advantageous.

The studentship covers fees and tax-free enhanced stipend for 4 years, and includes industrial placements at the supporting company. The successful candidate will receive full academic and professional training from the Wind & Marine Energy Systems & Structures Centre for Doctoral Training (WAMSS CDT). The Wind & Marine Energy Systems & Structures ( is an EPSRC-funded Centre for Doctoral Training, led by the University of Strathclyde, working collaboratively with Universities of Oxford and Edinburgh. The Centre aims to train the next generation of technical leaders, through EngD and PhD graduates, for the Offshore Renewable Energy (ORE) sector.

Desired candidate: 

  • Should be able to reliably develop and deploy machine learning pipelines for analysis of subsea structures 
  • Should be able to develop and maintain code in an organised and timely matter 
  • Contribute to additional concurrent projects at Ilosta Ltd.


Applicants should hold at least a first-class bachelor’s honours degree or MEng/MSc in the fields of machine learning, signal processing, software engineering, computer vision or other related fields.

  • Prior knowledge or experience in image processing, Python programming language, and machine learning packages is essential. 
  • Knowledge on point-cloud processing would be highly advantageous. 
  • Knowledge on 3D reconstruction techniques is advantageous. 
  • Experience in software for source control e.g., GitHub would be beneficial but not essential 
  • Ability to work independently, and form own goals and milestones.

For any enquiries about this vacancy please contact Professor Ali Mehmanparast ().

Computer Science (8)

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