PhD Position in Luleå University of Technology Sweden

PhD student in Operation and maintenance with specialization in Industrial Artificial Intelligence and eMaintenance – Lulea University, June 2022


The Luleå University of Technology invites applications for a Ph.D. position in Operation and maintenance is a rapidly growing research area, Sweden – June 2022

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General Info

Position: PhD Position
No. of Positions: 1
Research Field: , , ,
Deadline to Apply: Expired
Joining Date: ASAP
Contract Period: 4 Years
Salary: According to standard norms


Luleå University of Technology (LUT), Sweden


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Qualification Details

We are looking for an active person who has an interest in research studies, preferably with a background and experience in building mathematical models, optimization methods, simulation techniques, but also interest in metaheuristics, statistics, and machine learning. You must have an MSc degree from construction engineering, maintenance and operation engineering, computer science, applied physics, control technology, signal processing, or equivalent. You should have good knowledge of modeling and software development. You should also be proficient in programming languages such as Python, R, MATLAB, and their associated simulation and optimization libraries and packages. Construction experience, experience in the railway industry as well as knowledge in the maintenance area and software development are meritorious. Experience of Azure environment and platform and Azure AI services is also meritorious.

In order to communicate within the projects and with different stakeholders, we require you to master Swedish, in speech and in writing, and have good knowledge of speech and writing in English.

For further information about a specific subject see General syllabus for the Board of the faculty of science and technology

Responsibilities/Job Description

Operation and maintenance is a rapidly growing research area as it is recognized as an important enabler for the business performance by industry all over the world. For many industries maintenance costs are one of the biggest individual cost item. Effective maintenance can generate income for industry through better facility utilization and higher availability. Through well planned maintenance, external and internal operational risks can also be controlled and minimized.

Subject description

Operation and Maintenance Engineering deals with the development of methodologies, models and tools to ensure high system dependability and efficient and effective maintenance processes for both new and existing systems.The subject area of Operation and Maintenance Engineering is multidisciplinary in nature, transcending the boundaries and separating many disciplines of science, emerging technology and arts. The activities of the Division are aligned towards finding synergies with other engineering disciplines and building networks with many active research groups, locally and worldwide. The Division has been successful in obtaining grants from EU and Swedish Research funding agencies like VINNOVA and SSF. The Division has launched an International Journal of System Assurance Engineering and Management published by Springer. The establishment of SKF- University Technology Center for advanced condition monitoring has provided the Division with a much-needed platform for the development of predictive technology. Besides, two eMaintenance Labs are functioning at Luleå University of Technology and LKAB, Kiruna; a Condition Monitoring Lab has been established at the Division. The Division is fully competent and equipped technologically to undertake research work in the emerging areas of big data, predictive and prescriptive analytics.

Project description

In this position, you will mainly be working on one of our research projects called ‘AI Factory for Construction’, which focuses on research related to Industrial AI and eMaintenance in the construction industry, including Machine Learning, Transferred Learning, and Deep Learning. The project aims to facilitate the site management process in construction industry by developing and demonstrating solution based on Digital Twin approach empowered by AI and digital technologies.

This project will contribute to increased utilization of AI and digitalization of the construction industry, by conducting research within:

  • Industrial AI
  • Digital Twin
  • Nowcasting and forecasting
  • Machine Learning
  • Deep Learning
  • Business Intelligence- Big Data
  • Cloud/edge Computing
  • Information Logistics
  • Operation & maintenance
  • eMaintenance

The project will be carried out in close collaboration with representatives from the construction industry. The work will be carried out in a project form consisting of doctoral students, senior researchers and industry representatives.


You will be working in the research team of Industrial AI and eMaintenance. In this position you will also contribute to further development of our platform ‘AI Factory’ and enhance the capabilities in our lab ‘eMaintenance LAB’.

The work will include:

  •  Studies of relevant theoretical frameworks
  • Mapping needs and requirements from an industrial perspective- Identify and analyze gaps in industrial and academic contexts
  • Design of solutions, ink. methodologies, technologies, and tools
  • Development of AI algorithms, tools, and solutions using methods including but not limited to mathematical programming, metaheuristics, robust optimization, stochastic optimization.
  • Publication in academic journals and conferences
  • Participating as a lecturer and assistant in the Division’s courses

How to Apply?

Application Method: Online Application
Ref. No.: 1431-2022

Application Procedure

We prefer that you apply for this position by clicking on the apply button belowThe application should include a CV, personal letter and copies of verified diplomas from high school and universities. Mark your application with the reference number below. Your application, including diplomas, must be written in English or Swedish.

About the Employer:

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Contact details

Employment as a PhD student is limited to 4 years, teaching and other department duties may be added with max 20%. Placement: Luleå.For further information about the position, please contact Prof. Ramin Karim, +46 920-49 2344, [email protected]Union representatives:SACO-S Kjell Johansson (+46)920-49 1529 [email protected], OFR-S Lars Frisk, (+46)920-49 1792 [email protected]In case of different interpretations of the English and Swedish versions of this announcement, the Swedish version takes precedence.

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