PhD student position with a specialization in ??-?????? ?????????? ??? ???????????? ?? ?????????????.

University of Skövde; Skövde kommun; On-site; SEK 336,000 - 408,000; Full time

Job summary

University of Skövde in Sweden seeks a doctoral student to join a research team working on AI-driven, simulation-based decision support for resilient and sustainable production.

You will develop intelligent methods that help manufacturing companies maintain stable operations, improve energy efficiency, and adapt to disruptions and changing energy conditions, with close collaboration with industrial partners.

Qualifications

• Advanced degree required in Informatics or related field.
• 60+ ECTS at advanced level with independent thesis (15 ECTS) in related area.

Responsibilities

• Join a research team focused on AI-driven decision support for resilient production.
• Develop intelligent methods for energy-efficient, disruption-adaptive production planning.
• Collaborate with industrial partners to translate research into practical solutions.
• Contribute to both scientific knowledge and industrially applicable decision-support tools.

Skills

DES modeling

ML & RL

Python

C++

AI-based optimization

Predictive modeling

Discreteevent simulation

Industrial collaboration

Research planning

Education

Advanced degree in Informatics or related field

60+ ECTS at advanced level with thesis

Tools

Python

C++

Job description

Role Description The successful candidate will join a research team working on AI-driven, 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 optimization, 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, renewable energy use, and environmental performance.

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

The employment comprises full-time doctoral studies, including coursework and research.

Qualifications

• Obtained a degree at advanced level, or completed at least 240 higher education credits (ECTS), of which at least 60 credits are at the advanced level, or acquired essentially equivalent knowledge within or outside Sweden.
• Completed course requirements of at least 60 higher education credits (ECTS), including independent thesis work comprising at least 15 higher education credits at an advanced level, in the field of Informatics, related applied areas, or other subject areas deemed directly relevant to dissertation work within the field of Informatics such as computer science, information technology, industrial engineering, production engineering, automation technology, or other relevant subject areas.
• Documented English language proficiency equivalent to the Swedish upper secondary course English 6. This can also be demonstrated by an internationally recognized test such as IELTS (overall score of 6.5), TOEFL (total score of 90), PTE (total score of 62), etc.

We will also evaluate the candidates based on the following assessment criteria:

• Good ability to successfully undertake doctoral studies.
• Good knowledge and experience in modeling and simulation of manufacturing systems, such as discrete-event simulation (DES).
• Good knowledge and experience in machine learning, reinforcement learning, and AI-based optimization for production control.
• Good knowledge and experience in multi-objective optimization and predictive modeling.
• Proficiency in programming in Python, C++, or similar languages.
• Ability to work independently, plan and conduct research, and achieve set goals.
• Good communication and collaboration skills.
• Experience in industrial collaboration, applied research, or practical implementation.

In this employment, great emphasis will be placed on good knowledge and experience in modeling and simulation of manufacturing systems, such as discrete-event simulation (DES), as well as good knowledge and experience in machine learning, reinforcement learning, and AI-based optimization for production control.

Deadline for applications: November 8th 2026