Luleå University of Technology is in strong growth with world-leading competence in several research areas. We shape the future through innovative education and ground-breaking research results, and based on the Arctic region, we create global social benefit. 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 1.9 billion per year. We currently have 1,840 employees and 17,670 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.
Asset management, operation and maintenance is a rapidly growing research area as it is recognised as an important enabler for the business performance of industries worldwide. For many industries maintenance costs are one of the biggest individual cost items. Effective maintenance can generate income for the industry through better facility utilisation and higher availability. Through well-planned maintenance, external and internal operational risks can also be controlled and minimised.
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.
In this position, you will mainly be working on one of our research projects called ‘AI Factory /RAILWAY’, which focuses on research related to Industrial AI and eMaintenance in the railway domain. The project has a specific focus on Machine Learning, Transfer Learning, Deep Learning, Natural Neural Network, Spiking Neural, Graph technology, and quantum computing.
This project will contribute to increased utilisation of AI, digitalisation, quantisation of the railway industry, by conducting research within:
- Industrial AI
- Operation & maintenance
- Digital Twin
- Nowcasting and forecasting
- Machine Learning
- Deep Learning
- Big Data
- Cloud/edge Computing
- Quantum computing
- Graph technology
The project will be carried out in close collaboration with representatives from the railway industry and academia. The work will be carried out in a project form.
You as a PhD student will be working in the research team of Industrial AI and eMaintenance. In this position, you will also contribute to further developing our research concept and technology platform of ‘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 analyse 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 optimisation, and stochastic optimisation.
- Publication in academic journals and conferences.
- Participating as a lecturer and assistant in the Division’s courses.
- You as a PhD student must have an MSc in maintenance and operation engineering, data science, computer science, or equivalent.
- You should also have good knowledge of AI, computer science, cloud computing, and software engineering.
- We are looking for an active person interested in research studies.
- To communicate within the projects and with different stakeholders, we require you to master Swedish, in speeches and in writing, and have good knowledge of speech and writing in English.
- Experience in the railway industry.
- A background and experience in building mathematical models, optimisation methods, and simulation techniques, but also an interest in metaheuristics, statistics, and machine learning.
- You should be proficient in programming languages such as Python and C#, and their associated libraries and packages.
- You should be proficient in graph technology.
- You should be proficient in quantum development toolkits such as Q#, Qiskit, and Cirq.
- Domain knowledge of the railway industry is meritorious.
- Experience of Azure environment and platform and Azure AI services and is meritorious.
Employment as a PhD student is limited to 4 years, teaching and other department duties may be added with max 20%. Placement: Luleå. Starting date: 1 January 2024
For further information about the position, please contact: Ramin Karim, Professor, (+46) 920-49 2344, firstname.lastname@example.org
In the case of different interpretations of the English and Swedish versions of this announcement, the Swedish version takes precedence.
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: 10 December 2023
Reference number: 4835-2023
Caractéristiques de l'emploi