Postdoctoral fellow

At the University of Skövde, we work together, closely, and interdisciplinarily to create engagement, quality, and results on a vibrant campus. We take shared responsibility for tasks and work towards the organization’s goals. The university’s environment provides strong opportunities for close collaboration between institutions, departments, students, colleagues, and external partners.

The position is within the subject area of Informatics, which at the University of Skövde, is defined as the science that studies how information is represented, processed and communicated in artificial and natural systems and how such systems are used and developed in order to achieve usable and effective applications and solutions for individuals, organizations or society.

You will be part of the SAIL research group, whose research activities focus on AI-based modeling of complex systems, uncertainty management in deep learning, visual analytics, transparent decision-support systems, data protection, and recommender systems. SAIL is responsible for the University’s Master’s Programme in Data Science.

Your role

You will have a central role in the ongoing project ProcTwin that investigates how a distributed AI system can capture and predict the behavior of a production system under operational conditions. The project develops data collection, data storage, algorithms, and AI learning principles that allow components of a distributed AI system to be trained collaboratively to dynamically better cooperate toward a unified production outcome. The project includes twelve partners in Europe, with SSAB in Sweden and Celsa in Spain, two major steel producers where data will be collected and for which AI models will be developed. The postdoc position is central to the project in that you are expected to collaborate with project members to develop algorithms and knowledge within AI, through the development of experiments and simulations, and disseminate the results. You are expected to drive the development of publications that contribute to new knowledge within dynamic distributed AI systems, such that it contributes to the research area.

The principal duties of the position are to:

• Contribute to the ProcTwin project by independently leading work packages in collaboration with industrial partners and other project members.
• Design, implement and further develop research software, such as simulation environments, data pipelines and infrastructure, for the training and evaluation of machine learning models within distributed AI.
• Contribute to and take a leading role in the preparation of scientific publications within the field.
• Contribute to securing funding for, and carrying out, new research projects.
• Undertake teaching duties within the department in areas relevant to the post.

The post will primarily consist of research activities. Teaching and other administrative duties may be required for up to 20% of the appointment. Additional duties may be included as part of the appointment.

The position requires:

• A doctoral degree in Informatics, Computer Science, Data Science, or a corresponding qualification from abroad that is deemed equivalent to a doctoral degree.
• Documented research experience in artificial intelligence (AI), machine learning and data science, with applications in industrial systems.
• Excellent written and verbal communication skills in English.
• Strong collaborative skills, as well as the ability to build and maintain professional relationships and research networks.

We will also evaluate the following criteria when hiring:

Of highest importance are:

• A Doctoral degree completed no more than three years before the application deadline.
• The extent to which the applicant demonstrates the competencies required to meet the eligibility criteria.
• Documented ability to work independently and autonomously.
• Experience in the development of distributed AI or multi-agent systems based on current research.
• A relevant publication record.
• Experience in software development for research purposes within Informatics or Computer Science.

Of secondary importance are:

• Experience of industry-academia collaboration for research purposes, primarily within highly automated manufacturing industries handling large-scale datasets.

Also of importance:

• Experience in, or demonstrated potential for, teaching in areas relevant to the position.

Employment type: The position as a postdoctoral fellow is full-time and is made in accordance with the current collective agreement between the Swedish Employers' Agency, OFR-S, Saco-S and SEKO. The position is limited in time for two years.

Employment scope: Full-time (100%)

Application deadline: October 20st 2026

Registration number: Ref nr HS 2026/594

Access: By agreement

Contact Information: Information about the position is provided by Head of Department Jesper Holgersson (jesper.holgersson@his.se) and Associate Professor Gunnar Mathiason (gunnar.mathiason@his.se). Union information is provided by Anders Johansson (Saco-S) or Maria Carlstedt (ST). All persons can be reached via the University's switchboard 0500-44 80 00.

Application

You apply for the position via our website, www.his.se/jobb by clicking on "Apply" at the bottom of the advertisement. There you can also read more about the University's recruitment process and the benefits you have as an employee with us. We look forward to receiving your application!

The following documents must be attached to your application:

• Personal letter
• CV
• Certificates/grades and other qualifications you wish to submit in support of your application
• Portfolio of qualifications where you describe your scientific and educational activities
• Scientific publications, attach a maximum of five scientific publications (of which at least two were published in the last three years)
• Complete list of publications.

Contact the HR department at hr-specialister.hr@his.se if you have publications that cannot be attached electronically directly to the application. The publications must be received by the University no later than one week after the application deadline.