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 that you will help us build the sustainable businesses and communities of the future. The Department of Civil, Environmental and Natural Resources Engineering (SBN) offers unique and integrated research expertise in civil engineering. The research subject Civil Engineering is now looking for a motivated PhD student who wants to contribute to science and technology in assessment problems. In our doctoral program, we strive for you as a doctoral student not only to develop into an expert in the subject, but also to grow as an individual. Subject description Structural engineering deals with loads and deformations, design, dimensioning, durability, load-bearing capacity, repair and strengthening of buildings and civil engineering structures made of concrete, steel, wood and other materials, either individually or in combination, under normal conditions as well as in cold climates and in case of fire. Project description This project focuses on developing and implementing a bridge management platform that integrates AI, Big Data analytics and sensor monitoring to improve the efficiency and accuracy of bridge maintenance and monitoring processes. With an increasing need to ensure bridge infrastructure resilience and safety, the project aims to use data-driven techniques to predict structural health trends, optimize maintenance schedules, and minimize operational disruptions. You as a PhD student will work on designing algorithms and frameworks for collecting, processing and analyzing data in real-time, thus supporting decision-making processes in bridge management. In collaboration with ongoing monitoring efforts and existing data infrastructure, the project will explore the integration of machine learning techniques to analyze historical and current data for predictive maintenance and automated anomaly detection. This project will contribute significantly to the field of bridge management by providing scalable, adaptable and efficient tools for infrastructure safety. Work tasks A PhD position involves both theoretical and practical work. The PhD student will be trained in scientific work through the publication of scientific papers in journals and at national and international conferences. A doctoral student also takes compulsory and optional doctoral courses. In addition, you may have the opportunity to try out the role of teacher. As a researcher, you will work as a neutral party in many contexts, which provides a great opportunity to learn how to run challenging development projects. Qualifications As a PhD student, you will be expected to carry out both theoretical and field work in your research studies and to communicate your results at national and international conferences and in scientific journals. You are also expected to complete the mandatory PhD courses. Most of your working time is devoted to your own research studies. In addition, you may have the opportunity to try out the teaching role in the Mining Engineering and Mine Design and Planning courses. The requirements for this position: - Have an MSc in Civil Engineering or Computer Science or equivalent educational background in relevant subjects - Have experience in big data analytics - Have experience with low-level programming languages - Experience in writing scientific publications - Have good communication skills in English and Swedish, both oral and written. - Ability to use the following software: MS Office, Matlab, Graphing software. For further information on specific doctoral programs see, * Curricula for doctoral programs in the Faculty of Engineering Information to be provided Employment as a doctoral student is limited to 4 years, teaching and other departmental duties may be added up to 20% of full time. Location Luleå with start according to agreement. For further information, please contact: Chao Wang, Assistant, Senior Lecturer, 0920-49 2944 chao.wang@ltu.se, Jaime Gonzalez-Libreros, Associate Senior Lecturer, 0920-49 2970 jaime.gonzalez@ltu.se Trade union representative: 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 copies of verified diplomas. Please mark your application with the reference number below. Both the application and the diplomas must be written in Swedish or English. Deadline for applications: December 16, 2024 Reference number: 4602-2024