PhD student in Energy Engineering

5 days ago

Västerås, Västmanland, Sweden Mälardalens universitet Full time

Mälardalen University (MDU) is the youngest university in Sweden. In line with our vision, to be a progressive and collaborative University where we shape a sustainable future together, we wish to make a difference.

Do you want to be involved and contribute to our development?

Together, we can create a sustainable future through knowledge and innovation. We believe that knowledge and new perspectives are best attained and reached together in collaboration with others – our colleagues, students, the private and public sectors, both nationally and internationally.

At the school of Business, Society and Engineering, our students study for, among other things, university and civil engineers, political scientists and economists. With us, the research focuses are industrial economics and organization and the energy of the future. Our work takes place in collaboration and in strategic agreements with companies, organizations and authorities in the region.

Employment information

Employment: Temporary employment

Scope: Full time

Number of positions: 1

Closing date for application: 2025-04-30

Campus location: Västerås

School: School of Business, Society and Engineering, (EST)

Eligibility

Access to third-cycle courses and study programmes at a higher education education as well as basic eligibility requirements and assessment criteria, are regulated in the Higher Education Ordinance chapter 7.

A full-time employment as a doctoral student is attached to this third-cycle studies which corresponds to four years.

Position Description

The subject of Energy and Environmental Engineering is built up and developed by the research in the research specialisation of Future Energy. This research programme is mainly technologically oriented towards renewable energy as well as the efficiency of resources in the process industry and buildings. Studies carried out within the subject are experimentally or theoretically oriented.

The project focuses on innovating solid waste processing through AI (iWASTE), supported by AI@MDU initiative framework. The objective of this project is to develop new solutions for solid waste (SW) classification and utilization based on advanced AI technologies, such as regenerative AI, image processing and reinforcement learning, that can improve the energy efficiency and reduce the operating cost and emission of pollutants when using solid waste in CHP plants.

The PhD student is expected to take initiatives, develop own ideas and work independently when needed, as well as take responsibility for the work. Furthermore, the project interacts closely with other research projects and industrial partners. Thus, the applicant needs to have high collaborative skills. The PhD student needs to be able to disseminate and communicate scientific results and knowledge orally as well as in written form within existing and new networks. This includes academia, industry and society at large. The research results will be presented at project meetings, conferences and in peer-reviewed scientific journals.

Qualifications

To be eligible for doctoral studies, you must meet both the basic and specific eligibility requirements.

Basic eligibility requires one of the following:

  • A degree at the advanced level (Master's or equivalent).
  • At least 240 higher education credits, of which at least 60 must be at the advanced level.
  • Equivalent knowledge acquired through other means in Sweden or abroad.
Specific eligibility for this position requires one of the following:
  • A Master of Science in Engineering (Swedish: civilingenjör) or equivalent degree (at least 240 higher education credits) in Energy Engineering, Computer Science, Robotics, or Electrical and Computer Engineering.
  • A four-year natural science degree with technical content equivalent to a Master of Science in Engineering.
  • Equivalent knowledge acquired through other qualifications, either in Sweden or internationally.
Assessment criteria

Prior to employment, consideration must be given to the ability to assimilate third-cycle courses and study programmes at a higher education.

The applicant should have documented knowledge in energy systems and machine learning technologies. The position requires motivation for research, good oral and written communication, knowledge in English and a will to work in a multidisciplinary context and in collaboration with external partners. Decisive importance is attached to personal suitability. We value the qualities that an even distribution of age and gender, as well as ethnic and cultural diversity, can contribute to the organization.

Further qualifications and merits for the position are:
  • Knowledge and experience on image processing or computer vision.
  • Knowledge and experience on generative AI.
  • Knowledge of data driven methods for modelling and optimization.
  • Experience of multidisciplinary work and collaboration between academia and external partners.
  • Good programming skills in Python (Pytorch) etc.
  • Additional knowledge on waste and Near-infrared spectroscopy.
In an overall assessment of suitability, emphasis is also placed on personal abilities. All employees at MDU are expected to cooperate and treat colleagues and students with respect, take responsibility for the organisation and their own work duties and contribute to a positive work environment.

Application

The application is to be completed online. Please submit your application by clicking on the "Apply" button below.

The applicant is responsible for ensuring that the application is complete in accordance with the advertisement and will reach the University no later than closing date for application.

We look forward to receiving your application.

Union representatives:

Saco-S saco-s@mdu.se

Susanne Meijer ST-OFR/S, tel: 021-10 14 89

We decline all contact with recruiters and sellers of advertisements. We have made our strategic choices for this recruitment.

Contact person

Anders Avelin

Avdelningschef

+46 (0) 21-15 17 98

anders.avelin@mdu.se

Hailong Li

Professor

+46 (0) 21-10 31 59

hailong.li@mdu.se
#J-18808-Ljbffr

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