Department of Computer and Systems Sciences
With over 200 employees and 4,500 students, the Department of Computer and Systems Sciences (DSV) provides a strong and dynamic research and educational environment. The field of computer and systems sciences intersects technology, humanities, social sciences, and behavioral sciences, with significant relevance to our lives today and in the future. Our research focuses on how new information and communication technologies can be designed to benefit individuals, organizations, and entire societies.
DSV offers an inspiring research community in an international environment. Many of our projects are interdisciplinary, and our researchers frequently collaborate with colleagues at other institutions, in the private sector, and within public organizations. Our research is conducted in nine areas: Business Processes and Enterprise Modeling, AI and Data Science, Cybersecurity, Digital Games and Simulation, Digital Transformation and Governance, Human-Computer Interaction, Language Technology, Risk and Decision Analysis, and Technology-Enhanced Learning.
For more information about us, visit: https://www.su.se/institutionen-for-data-och-systemvetenskap/.
Project Description
Artificial Intelligence (AI) is a rapidly growing research area that leverages technologies such as machine learning, statistics, and decision support. In particular, developments in deep learning and reinforcement learning in recent years have resulted in high-performing models and tools for complex applications. At the same time, the concept of a digital twin has become central throughout the lifecycle of system development, from design and planning to operation, monitoring, and optimization of products and services. A data-driven digital twin can be defined as a digital representation of a physical system or service, where live data continuously streams in to enable monitoring, time series forecasting, explainability, and decision-making. This postdoctoral project aims to combine artificial intelligence and machine learning methods, with a particular emphasis on time series forecasting and explainable machine learning, alongside the conceptual architecture and prototypes of digital twins. The primary objective is to develop methods that can support the healthcare sector, for example through predicting patient trajectories, resource needs, and real-time support for care decisions. Additionally, these methods can also be applied to smart buildings, where digital twins can be utilized for energy optimization and improved indoor environments. The project will use real-time streaming data from these domains to ensure both scientific utility and practical relevance.
The postdoctoral researcher will be placed in https://www.su.se/forskning/forskargrupper/data-science-research-group, which has high expertise in the field of explainable machine learning.
Duties
As a postdoctoral researcher, you will:
- Conduct independent and collaborative research within AI for digital twins.
- Develop methods and algorithms for time series analysis, prediction, and decision support in healthcare and smart buildings.
- Participate in collaborations with researchers, clinical partners, and industry partners.
- Publish research findings in international journals and conferences.
- Contribute to teaching and supervision at the undergraduate and master’s levels within the department.
The position entails 80% research and 20% teaching.
Eligibility Requirements
To be eligible for the position of postdoctoral researcher, a completed doctorate or foreign degree assessed to be equivalent to a relevant doctoral degree is required. The degree must be obtained no later than at the time the employment decision is made.
Assessment Criteria
It is advantageous if the doctorate or equivalent has been obtained within three years preceding the application deadline. If there are special circumstances, a previously obtained degree may also be considered advantageous. Special circumstances include leave due to illness, parental leave, elected duties within trade union organizations, service in the total defense, or other similar circumstances, as well as clinical service or service/assignments relevant to the subject area.
In the employment process, particular emphasis will be placed on scientific expertise and a strong publication record in the fields of machine learning and data mining.
About the Position
The position is full-time and is limited to two years, with the possibility of extension if there are special reasons. Start date is November 15, 2025, or by agreement.
We Offer
At our department, you will experience the dynamic interplay between higher education and research that makes Stockholm University an exciting and creative environment. You will work in an international setting and enjoy advantageous conditions.
Stockholm University is committed to being a workplace free from discrimination and providing equal rights and opportunities for all.
Contact
Inquiries regarding the position can be directed to the head of the department, Professor Jelena Zdravkovic, email:
[email protected], or Professor Panagiotis Papapetrou, email:
[email protected].
Application
You apply for the position via Stockholm University’s recruitment system. Attach a personal letter and CV, along with the requested attachments in the application form. As the applicant, you are responsible for ensuring that your application is complete and submitted to the university by the application deadline.
Instructions for applicants can be found on the webpage: https://www.su.se/om-universitetet/jobba