PhD in Information Technology

Original title: Doktorand i informationsteknologi

Translated from Swedish by Graduates Corner. The official posting is the authoritative version.

The University of Skövde is a central, leading actor in education, research and collaboration that supports the transition to a sustainable future – regionally, nationally and internationally. Our 12,000 students and 460 staff create the conditions for society's digital transformation and sustainable development through high-quality education and research in selected areas. Welcome to a vibrant campus in the heart of Skaraborg.

The School of Engineering Science at the University of Skövde has a creative and dynamic environment with a very good climate for collaboration, modern facilities and excellent industrial cooperation. For more than a decade, the school has shown how a "smaller" university can achieve excellent applied research and high-quality education, and generate the funding and technical innovations that characterise a successful research environment. We work with an integrated education value chain with recognised added value for students: our new engineering programmes follow the CDIO framework, and students have good opportunities for placements and jobs with our industrial partners. The right candidate will join a team whose work is of great importance to industry, society and academia.

The doctoral studies are in the subject of information technology, which the University of Skövde defines as the subject dealing with how information is represented, processed and communicated in artificial and natural systems, and how IT systems are used and developed to achieve useful system solutions for individuals, organisations or society.

You will join a research group working on AI-driven and simulation-based decision support for resilient and sustainable production. As a doctoral student, you will develop intelligent methods that help manufacturing companies maintain stable operations, improve energy efficiency and adapt to disruptions and changing energy conditions.

The project will combine digital twins, discrete-event simulation, predictive modelling, multi-objective optimisation and AI-based decision support to support production planning and control. The research will address production sequencing, resource allocation, energy-aware scheduling and disruption management, with possible use of coordinated multi-agent AI systems to balance productivity, resilience, energy cost, use of renewable energy and environmental performance.

The work will be carried out in close collaboration with industrial partners and is expected to contribute both scientific knowledge and practical decision-support solutions for the manufacturing industry.

The position comprises full-time doctoral education, including courses and research.

a second-cycle degree, or completed courses of at least 240 credits of which at least 60 credits are at second-cycle level, or substantially equivalent knowledge acquired in Sweden or abroad

completed courses of at least 60 credits, including an independent thesis of at least 15 credits at second-cycle level, in information technology, closely related application areas or other subjects judged directly relevant to thesis work in information technology, such as computer science, information technology, production engineering, industrial engineering, automation engineering or another relevant field.

documented English language skills equivalent to the Swedish upper-secondary course English 6. This can also be shown through an internationally recognised test such as IELTS (overall score 6.5), TOEFL (total score 90), PTE (total score 62), etc.

We will also consider the following assessment criteria:

Good ability to benefit from doctoral education.

Good knowledge of and experience with modelling and simulation of manufacturing systems, for example discrete-event simulation.

Good knowledge of and experience with machine learning, reinforcement learning and AI-based optimisation for production control.

Good knowledge of and experience with multi-objective optimisation and predictive modelling.

Good programming skills in Python, C++ or similar languages.

Ability to work independently, plan and carry out research, and achieve set goals.

Good communication and collaboration skills.

Experience of industrial collaboration, applied research or practical implementation.

For this position, great weight will be placed on good knowledge of and experience with modelling and simulation of manufacturing systems, such as discrete-event simulation, and with machine learning, reinforcement learning and AI-based optimisation for production control.

The position is fixed-term until the doctoral degree is awarded, but for no more than 4 years. It is full-time (100%). Salary follows the local agreement on the salary scale for doctoral students. Only a person admitted, or already admitted, to doctoral education may be employed as a doctoral student.

Application deadline: 8 November 2026

Reference number: HS 2026/531

Attach the following documents to your application:

A cover letter including a statement of interest in which you describe, in English, your motivation, research interests and expectations of doctoral education

Certificates, grades and other documents you wish to refer to

Degree certificates and transcripts

Your one-year or two-year master's thesis

Contact the HR department at hr-specialister.hr@his.se if you have publications that cannot be attached electronically. Publications must reach the university no later than one week after the application deadline.

Contact: for information about the position, contact Head of Division Stefan Ericson (stefan.ericson@his.se) and Associate Professor Masood Fathi (masood.fathi@his.se). Union information is provided by Anders Johansson (Saco-S) or Maria Carlstedt (ST). All can be reached via the university switchboard on +46 500-44 80 00.

Apply via our website, www.his.se/jobb, by clicking "Apply" at the bottom of the advertisement. There you can also read more about the university's recruitment process and the benefits of working with us. We welcome your application!