PhD Project in Operation and Maintenance Engineering

Luleå University of Technology is experiencing strong growth with world-leading expertise in several research areas. We shape the future through innovative education and groundbreaking research results, and based on the Arctic region, we create global societal benefits. Our scientific and artistic research and education are conducted in close collaboration with international, national, and regional companies, public actors, and leading universities. Luleå University of Technology has a total turnover of 2 billion SEK per year. We currently have 1,500 employees and 17,900 students.

In the coming years, multi-billion investments will be made in Norrbotten and Västerbotten in large projects aimed at a more sustainable society both nationally and globally. Luleå University of Technology is involved in several of these highly relevant research projects and the societal transformation that follows. We have a wide range of educational programs to match the skills that are in demand. We hope that you will help us build the sustainable companies and societies of the future.

Operation and maintenance is a rapidly growing research area and an important field within many industries where maintenance costs are one of the largest individual cost items. Effective maintenance can generate income for the industry through better asset 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 includes the development of technologies to ensure high operational reliability, efficient maintenance processes, and lifecycle management of systems and facilities.

Project Description

This PhD project aims to promote the railway transport sector through the development of innovative methods for condition monitoring for both railway vehicles and railway tracks. This research will study sensor systems that generate data from various components of the railway infrastructure and from trains. The focus of the research will be on distributed fiber optic sensors and their combination with machine learning methods. The goal is to create predictive maintenance models that can proactively identify potential problems, thereby reducing downtime, minimizing maintenance costs, and ultimately improving the overall performance and sustainability of railway systems. The project will be linked to ongoing EU research projects, where real case studies applied to railway sections and existing vehicles will be used to validate the developed methods. The purpose of the research is to contribute valuable insights and generate knowledge in the field of transport engineering by improving maintenance boundaries for vehicles and track infrastructure, paving the way for a more sustainable and efficient railway infrastructure.

Job Responsibilities

The tasks within the PhD project include active participation in research and development of results and deliverables related to EU projects. In addition to theoretical thesis work, practical work related to database management, computer programming, and simulation will be included. Other tasks related to the doctoral education will be specified in the individual doctoral education plan.

For further information about specific doctoral education, see; Study plans for doctoral education within the Faculty of Technology.

Qualifications

To be eligible for employment, you must have a master's degree in computer science, mathematics, mechanics, geophysics, or similar education. You must also be able to speak and write fluent English. Subjects within your education that will be considered meritorious are:

• Signal processing
• Wave propagation
• Acoustic microphone arrays and structural sound
• Mechanical vibrations
• Computer programming
• Machine learning/artificial intelligence
• Predictive methods and computer science
• Railway system engineering

Information

Fixed-term full-time employment for four years. Institutional duties such as teaching may be added up to a maximum of 20% of full-time. Security clearance of the applicant may be required. The place of employment is Luleå. Start date by agreement.

For further information about the position, please contact Matti Rantatalo, Associate Professor 0920-49 2104, [email protected]

Union Representatives:

SACO-S Diana Chroneer, 0920-49 2037 [email protected]
OFR-S Lars Frisk, 0920-49 1792 [email protected]

Application

We prefer that you apply for the position via the application button below, where you attach a cover letter and CV/resume and diploma. Please mark your application with the reference number below. Applications and diplomas must be written in Swedish or English.

Application deadline: January 31, 2025
Reference number: 83-2025