Doctoral student in electrical engineering – Digital twins

The University of Gävle is looking for two PhD students in electrical engineering for the project Real-time analysis and optimization with digital twins, part of the Twin Transition initiative. The project develops digital twins for condition monitoring and predictive/prescriptive maintenance, focusing on the industry's need for digitalization and sustainability. The work combines machine learning, control engineering, system identification, experimentation and industrial collaboration.

The PhD positions are part of a larger research initiative that provides SMEs with access to cutting-edge expertise, test environments and research collaborations. The research contributes to the circular economy by reducing waste, increasing availability and extending the lifetime of technical systems.

About the workplace

The vision of University of Gävle is to be the first choice for all who want to make a difference. We offer around 60 study programmes and 330 freestanding courses in the fields of the humanities, health care and medicine, social and natural sciences and technology. University of Gävle is one of the most popular university colleges in Sweden (applicants per place). We have around 19 000 students, 750 employees, and our campus is concentrated in space in beautiful surroundings.

The university focuses on four strategic research areas - sustainable urban development, health promotion, innovative learning and intelligent industry.

We offer
- the opportunity to work at one of Sweden's most beautiful universities,
- a workplace with many employment benefits,
- a university that actively works on issues such as our common working environment, clear working conditions and gender equality and equal opportunities

The Department of Electrical Engineering, Mathematics and Natural Sciences educates engineering students, teacher trainees and foundation year students. The largest research group works in electrical engineering, automation and the strategic research area Intelligent Industry.

Work tasks

Position1 - Experimental modeling:

The project focuses on the development of digital twins (DT) for monitoring, fault analysis and predictive maintenance of complex manufacturing systems. The goal is to create solutions that work under realistic industrial conditions, where common challenges include weak excitation, feedback control systems, varying production conditions and communication between automation systems.

The research project combines physical modeling, machine learning and signal processing, and includes:

- Building an experimental lab with two-way communication between physical and digital environment.

- Modeling of components in complex manufacturing systems using hybrid methods (physics-based and data-driven).

- Development of robust machine learning methods for condition monitoring, fault identification and predictive maintenance.

Position 2 - Decision Support and Simulation:

This position focuses on developing a framework for risk-informed decisions in maintenance strategies. You will work with simulations and machine learning models (e.g., neural networks) to estimate uncertainty in decision data and optimize interventions based on state-action costs. The focus is on:

- Development of simulations that reflect real manufacturing conditions.

- Investigation and development of machine learning architectures to estimate State-Action Cost.

- Evaluation of the trade-off between model size, accuracy, risk and computational cost.

- Development of a tool for sizing models in practical applications.

The PhD positions include:

- carrying out the scientific project

- carrying out courses equivalent to at least 75 credits

- teaching and carrying out administrative work

- participating regularly in academic activities such as seminars and meetings

For the positions, the workplace is at the University of Gävle where most of the working hours are spent on campus.

Qualifications

To be admitted to doctoral studies (Chapter 7, Section 39 of the Higher Education Ordinance), the applicant must have

- completed a degree at second-cycle level or another specialization that the employer considers equivalent

- completed course requirements of at least 240 higher education credits, of which at least 60 higher education credits at second-cycle level, or in some other way acquired essentially equivalent knowledge within or outside the country.

In order to be admitted to doctoral studies in the subject of electrical engineering, the following are required in accordance with the current general syllabus: Master's degree in electrical engineering or equivalent.

Meritorious for the doctoral positions are:

- A focus on machine learning, optimization, modelling/simulation, signal processing and/or control engineering

- Experience of practical experimental work in a laboratory environment

- Ability to use MATLAB and/or Python

- Knowledge of control systems and sensor systems, preferably in connection with hydraulics

To succeed in your doctoral studies, you should be self-motivated and have the ability to drive your work forward. You have a good ability to collaborate with others, have a professional approach and have the ability to analyze and work with complex issues. As a research student, you should have a willingness to seek new knowledge and also be able to explain and discuss research with people who are not active in your own subject, both nationally and internationally. Furthermore, you have good ability to express yourself in speech and writing in English. Good knowledge of Swedish is a merit.

Selection of applicants for a place on a course is based on the overall assessment of the applicant's ability to benefit from the course.

Information on admission and employment:

Only those admitted to doctoral studies may be employed as doctoral students. The total period of employment may not exceed the equivalent of four years of full-time doctoral education. A new appointment as a doctoral student is valid for a maximum of one year, after which the appointment may be renewed for a maximum of two years at a time.

Conditions for application

Applications must include a CV, a covering letter and any other documents, such as diplomas, that you wish to refer to.

Contact person

Mikael Cronhjort

Head of department, The Department of Electrical Engineering, Mathematics and Natural Sciences

+4626-648402

mikael.cronhjort@hig.se