PhD student position for AI Factory /AVIATION in Operation and maintenance – Luleå, Sweden

Suède
Posted 9 Monaten ago

Ref 3325–2023

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.

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.

Project description
In this position, you will mainly be working on one of our research projects called ‘AI Factory /AVIATION’, which focuses on research related to Industrial AI and eMaintenance in the aviation industry, including Machine Learning, Transfer Learning, Deep Learning, Natural Neural Network, Spiking Neural Network etc.

This project will contribute to increased utilisation of AI and digitalisation of the aviation 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.

Duties
The selected candidate will be working in the research team of Industrial AI and eMaintenance. In this position you will also contribute to the further development of our platform ‘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

Qualifications

  • Applicants must have an MSc in maintenance and operation engineering, data science, computer science, applied physics, control technology, signal processing, or equivalent.
  • Applicants should have good knowledge of modelling and software development.
  • Aviation experience is meritorious.
  • 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 aviation 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, optimisation methods, and simulation techniques, but also an interest in metaheuristics, statistics, and machine learning.
  • The candidate should be proficient in programming languages such as Python, R, MATLAB, and their associated simulation and optimisation libraries and packages.

Further information
Employment as a PhD student is limited to 4 years, teaching and other department duties may be added with max 20%. Placement: Luleå. 1 November 2023.

For further information about the position, please contact Professor, 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 the 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: September 15 2023
Reference number: 3325-2023

Job Features

Job CategoryDoctorat

Apply Online

Check Also

Bourse d’excellence internationale de l’Université de Sienne 2024-25

Bourses d’excellence internationales de Sienne Conformément aux initiatives visant à renforcer l’attractivité internationale de ses …