Luleå University of Technology experiences rapid growth with world-leading expertise within several research domains. We shape the future through innovative education and groundbreaking research results and drawing on our location in the Arctic region, we create global societal benefit. Our scientific and artistic research and education are carried out in close collaboration with international, national and regional companies, public actors and leading universities. Luleå University of Technology has an annual turnover of SEK 1.9 billion. Today, we have 1,815 staff and 19,155 students.
In the coming years, multi-billion investments will be made in large projects in Northern Sweden to create a fossil-free society both nationally and globally. Luleå University of Technology is involved in several of these cutting-edge research projects and in the societal transformation that they entail. We offer a broad range of courses and study programmes to match the skills in demand. We hope that you will help us to build the sustainable companies and societies of the future.
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 LTU 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 Mining’, which focuses on research related to Industrial AI and eMaintenance in the mining industry, including Machine Learning, Transferred Learning, and Deep Learning. The project aims to facilitate the decision-making in operation and maintenance by developing and demonstrating solutions based on the Digital Twin concept, empowered by AI and digital technologies.
This project will contribute to increased utilization of AI and digitalisation of the mining 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.
For further information about a specific subject see; General curricula for the Board of the faculty of science and technology
Duties
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 mainly include:
– Studies of relevant theoretical frameworks
– Mapping needs and requirements from an industrial perspective
– Identify and analyses 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
Qualifications
In order to be eligible for employment you must have an MSc degree from maintenance and operation engineering, computer science, applied physics, control technology, signal processing, or equivalent.
– You should also have good knowledge of modeling and software development.
– Mining experience is meritorious.
– We are looking for you who have a strong interest in research studies.
– In order to communicate within the projects and with different stakeholders you must master Swedish, speeches and in writing, and also have good knowledge of speech and writing in English.
– Experience in the mining industry as well as knowledge in the maintenance area and software development are meritorious.
– Experience of Azure environment and platform and Azure AI services and is meritorious.
– A background and experience in building mathematical models, optimization methods, simulation techniques, but also interest in metaheuristics, statistics, and machine learning.
– You should be proficient in programming languages such as Python, R, MATLAB, and their associated simulation and optimization libraries and packages.
Further information
Fixed term employment for four years. Departmental duties such as teaching may be added up to maximum 20 % of fulltime. Placement: Luleå.
For further information about the position, please contact Prof. Ramin Karim, +46 920-49 2344, ramin.karim@ltu.se
Union representatives: SACO-S Kjell Johansson (+46)920-49 1529 kjell.johansson@ltu.se, OFR-S Lars Frisk, (+46)920-49 1792 lars.frisk@ltu.se
In case of different interpretations of the English and Swedish versions of this announcement, the Swedish version takes precedence.
Application
We prefer that you apply for this position by clicking on the apply button below. The 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.
Closing date for applications: July 30, 2022
Reference number:2265-2022
URL to this pagehttps://www.ltu.se/ltu/Lediga-jobb?l=en&rmpage=job&rmjob=5823&rmlang=UK