Postdoctoral Fellow in Explainable machine learning for digital twins

THe The Department of Computer and Systems Sciences. With over 200 employees and 4,500 students, the Department of Computer and Systems Sciences (DSV) is a strong and dynamic research and educational environment. The discipline of computer and systems sciences bridges the gap between technology and the humanities, social sciences, and behavioral sciences, with great relevance to our lives today and in the future. Our research addresses how new information and communication technology should be designed to benefit people, organizations and entire societies.

DSV offers a stimulating research community in an international environment. many of our projects are interdisciplinary, and our researchers frequently collaborate with colleagues at other universities, in industry, and within the public sector. Our research is conducted within nine subject areas: AI and Data Science, Business Process Management and Enterprise Modeling, Cybersecurity, Digital Games and Simulation, Digital Transformation and Governance, Human-Computer Interaction, Language Technology, Risk and Decision Analysis, and Technology-Enhances Learning. DSV´s current location is Stockholm University´s campus in Kista, north of central Stockholm, and we will move to the mail Frescati campus within a couple of years.

More information about us, please visit: the Department of Computer and Systems Sciences.

Project description

Artificial Intelligence (AI) is a rapidly growing research field that draw on technologies such as machine learning, statistics, and decision support. In recent years, developments in deep learning and reinforcement learning have resulted in high-performing models and tools for complex applications. At the same time, the concept of the digital twin has become central throughout the system development lifecycle - from design and planning to operation, monitoring, and optimization of product and services. A data-driven digital twin can be described as a digital representation of a physical system or service, continuously updated by live data streams 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 focus on time series forecasting and explainable machine learning, together with the conceptual architecture and prototypes of digital twins. The main objective is to develop methods that can support the healthcare sector, for example through prediction of patient trajectories, resource needs, and real-time clinical decision support. As a complement, the methods may also be applied to smart buildings, where digital twins can be used for energy optimization and improved indoor environments. The project will make use of real-world, streaming data from these domains to ensure both scientific impact and practical relevance.

The Postdoctoral researcher will be places in the data science group of DSV which has high expertise in the area of explainable machine learning.

Main responsibilities

As a postdoctoral researcher, you will:

• Conduct independent and collaborative research on AI for digital twins.
• Develop methods and algorithms for time series analysis, prediction, and decision support in healthcare and smart buildings.
• Collaborate with researchers, clinical partners, and industry partners.
• Publish research results in international journals and conferences.
• Contribute to teaching and supervision at the undergraduate and master’s level at the department.

The position consists of 80 % research and 20 % teaching.

Qualification requirements

In order to qualify for a Postdoctoral position, applicants are required to hold a Swedish doctoral degree or an equivalent relevant degree from another country. The degree must have been completed no later than when the employment decision is made.

Assessment criteria

It is considered an advantage if the doctoral degree or an equivalent degree was completed no more than three years prior to the application deadline. Under special circumstances, an older degree may also be an advantage. Special circumstances refer to sick leave, parental leave, elected positions in trade unions, service in the total defense, or other similar circumstances, as well as clinical attachment or service/assignments relevant to the subject area.

In the appointment process, special attention will be given to research skills and a strong publication record in the area of machine learning and data mining.

About the employment

The position involves full-time employment for two years, with the possibility of extension under special circumstances. Start date 2025-11-15 or as per agreement.

We offer

With us, you will experience the dynamic interaction between higher education and research that makes Stockholm University an exciting and creative environment. You will work in an international environment and get favourable conditions.

Stockholm University strives to be a workplace free from discrimination and with equal opportunities for all.

Contact

Further information about the position can be obtained from the Head of the Department, Professor Jelena Zdravkovic, jelenaz@dsv.su.se, or Professor Panagiotis Papapetrou, panagiotis@dsv.su.se.

Application

Apply for the position at Stockholm University's recruitment system. Attach a personal letter and CV as well as the attachments requested in the application form. It is the responsibility of the applicant to ensure that the application is complete in accordance with the instructions in the job advertisement, and that it is submitted before the deadline.

The instructions for applicants are available at: How to apply for a position.