Luleå University of Technology is growing rapidly 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 social 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 SEK 2 billion per year. We are currently 1,500 employees and have 17,900 students. In the coming years, billions of kronor will be invested in Norrbotten and Västerbotten in major projects aimed at a more sustainable society nationally as well as globally. Luleå University of Technology is involved in several of these highly topical research projects and the social transformation that follows. We have a wide range of programs to match the skills that are in demand. We hope you will join us in building the sustainable businesses and communities of the future. Operation and maintenance is a rapidly growing field of research and an important area in many industries where maintenance costs are one of the largest single cost items. Efficient maintenance can generate revenue for industry through better asset utilization and higher availability. Through well-planned maintenance, external and internal operational risks can also be controlled and minimized. The subject area/Department of Operation and Maintenance Engineering is multidisciplinary in nature, incorporating many scientific disciplines and new emerging technologies. The activities of the division are geared towards finding synergies with other engineering disciplines and building networks with many active research groups, locally and globally. The division has been successful in obtaining grants from the EU and Swedish research funders such as VINNOVA and SSF. The division has launched a scientific journal "International Journal of System Assurance Engineering and Management" published by Springer. The establishment of the SKF University Technology Center for Advanced Condition Monitoring has created a platform for the development of predictive technologies and condition monitoring. The department has an eMaintenance lab and a condition monitoring lab with associated test facility for railway components. The department is also fully competent and technically equipped to carry out research work in the emerging areas of big data, predictive and prescriptive analytics. Subject description Operation and Maintenance Engineering covers the development of technologies to ensure high reliability, efficient maintenance processes, and life cycle management of systems and facilities. Project description This PhD project aims to advance the field of rail transportation through the development of innovative methods for condition monitoring for both rail vehicles and rail tracks. This research will study sensor systems that generate data from different components of the railway infrastructure and from the trains. The focus of the research will be on distributed fiber optic sensors and the 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 aim of the research is to contribute valuable insights and generate knowledge to the field of transportation engineering by improving the maintenance limits of vehicles and track infrastructure, paving the way for a more sustainable and efficient railway infrastructure. Work tasks The tasks within the PhD project include active participation in research and development of results and deliverables linked to EU projects. In addition to the 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 on specific doctoral education see; Study plans for doctoral education in the Faculty of Engineering Qualifications To be eligible for employment, you must have a Master's degree in the subject of 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 as merits are: - Signal processing - Wave propagation - Acoustic microphone arrays and structure-borne sound - Mechanical vibrations - Computer programming - Machine learning/artificial intelligence - Prediction Methods and Data Science - Railway systems engineering Information Technology Fixed-term full-time position for four years. Institutional duties such as teaching may be added up to a maximum of 20% of full-time. Security check of the applicant may be done. Place of employment is Luleå. Access according to agreement. For further information about the position, please contact Matti Rantatalo, Assistant Professor 0920-49 2104, matti.rantatalo@ltu.se Trade union representatives: SACO-S Diana Chroneer, 0920-49 2037 diana.chroneer@ltu.se OFR-S Lars Frisk, 0920-49 1792 lars.frisk@ltu.se How to apply We prefer that you apply for the position via the application button below where you attach a cover letter, CV/resume and diploma. Please mark your application with the reference number below. The application and diploma must be written in Swedish or English. Deadline for applications: January 31, 2025 Reference number: 83-2025