Postgraduate research opportunities Ship machinery intelligent diagnostics and maintenance by integrating digital twins and mixed reality tools


Key facts

  • Opens: Monday 21 February 2022
  • Deadline: Friday 30 September 2022
  • Number of places: 1
  • Duration: Starts in October 2022, for 3 years.
  • Funding: Home fee, Stipend


This PhD project aims to develop a novel methodology and associated tools to address the intelligent diagnostics and cost-effective maintenance of critical ship machinery systems by integrating digital twins and virtual/mixed reality tools.
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We're looking for an outstanding and enthusiastic PhD student with a Masters degree (MEng or BEng & MSc) and pertinent expertise in one or more of the following areas:

  • marine systems engineering
  • systems modelling
  • safety, reliability and maintenance engineering
  • machine learning
  • virtual reality

The candidate should be able to undertake, complete and disseminate the outcomes of this research in international conferences and high-impact research journals.

Applicants should have a distinction pass at Masters level in:

  • naval architecture & marine engineering
  • maritime technology/engineering
  • (digital) manufacturing and production
  • engineering
  • mechanical aerospace engineering
  • other relevant areas
THE Awards 2019: UK University of the Year Winner
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Project Details

The project targets to achieve intelligent operations of maritime assets by using industry 4.0 technologies such as:

  • digital twins
  • virtual/mixed reality
  • machine learning tools

The aim is to shift the decision-making process from vessel to shore, and from humans to machines, with reduced crew intervention, thus progressing towards more sustainable and autonomous operations. The project ambition is to address the maritime industry challenges pertinent to the rapid growth and use of smart technologies, automated and autonomous systems operations, as well as acquired data trustworthiness.

This project plans to develop solutions enabling the integration and use of smart technologies to achieve optimal and cost-effective maintenance of critical ship machinery systems, thus catalysing the effective decision-making for smart land-controlled ship operations management.

Four key pillars will be considered:

  • intelligent and optimal ship machinery maintenance planning
  • machine learning-enabled operations
  • data trustworthiness combining measurements with virtual sensors
  • the use of virtual and mixed reality tools for robust decision-making

Further information

The project is collaborative between the Maritime Safety Research Centre (MSRC) at the Department of Naval, Architecture, Ocean & Marine Engineering (NAOME) and the National Manufacturing Institute Scotland (NMIS), both at University of Strathclyde.

The proposed research complements the research activities carried out at the MSRC, focused on the development of intelligent systems advancing net-zero shipping operations as well as the themes of data analytics and digital factory of NMIS. The NMIS state-of-the-art digital visualisation suite and Interactive 3D visualisation systems along with MSRC VR equipment will be employed throughout the project.

The Department of Naval Architecture, Ocean & Marine Engineering is a world-leader in research, whose main interests lie in:

  • maritime safety
  • marine hydrodynamics
  • marine structures
  • ocean engineering
  • marine engineering
  • emerging technologies
  • offshore renewable energy and alternative fuels

The Department makes a significant contribution to national, European and international policy-making in marine technology research and its application.

As part of a significant industry-University partnership involving, the University of Strathclyde, the Department of Naval Architecture, Ocean and Marine Engineering, Royal Caribbean Cruise Lines and DNV Classification Society, the Maritime Safety Research Centre (MSRC) of Excellence was established with the vision to shape the future of maritime safety.

The University of Strathclyde’s Advanced Forming Research Centre (AFRC) is a specialist technology centre within the National Manufacturing Institute Scotland. Filling the space between fundamental academic research and industry, AFRC provides access to cutting-edge R&D facilities and talented engineers, researchers and business professionals, who are securing the manufacturing sector in Scotland and the UK for generations to come.

Student experience & training

The student is expected to undertake the Researcher Development Programme (RDP) at the University of Strathclyde. The student will also have the opportunity to present his/her research in international conferences as well as seminars/workshops at MSRC and NMIS. A great effort will be put on collaborating and interacting with the ongoing research projects (e.g., i-HEATS) providing hands-on experience to the student.

Upon completion of the project, the student is expected to be in the forefront of state-of-the-art for intelligent maintenance of ship machinery systems, digital twins and VR/MR tools, thus having a significant advantage for further career development.

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Funding details

The funding covers the home student tuition fees and stipend in line with the UK Research Councils rates (£15,840 for academic year 2022-2023) for 36 months.

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Professor Gerasimos Theotokatos

Naval Architecture, Ocean and Marine Engineering

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Mr Syed Awais Munawar

Visualisation Theme Lead
Digital Factory

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Applicants should send their application directly to Ms Yun-Ting Hsieh –

Applications should include:

  • Cover Letter;
  • CV with two references;
  • Degree transcripts and certificates (in English), and if English is not your native language, a copy of your English language qualifications (IELTS).
  • Research proposal

The applicants need to demonstrate excellent organisational, interpersonal, verbal and academic writing skills.

An interview will be arranged for the shortlisted applicants.

To read how we process personal data, applicants can review our 'Privacy Notice for Student Applicants and Potential Applicants' on our Privacy notices web page.

Number of places: 1

An interview will be arranged for the shortlisted applicants.

To read how we process personal data, applicants can review our 'Privacy Notice for Student Applicants and Potential Applicants' on our Privacy notices' web page.

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Contact us

If you wish to discuss any details of the project informally, please contact Prof Gerasimos Theotokatos –