Uppsala University, Department of Information Technology

The Department of Information Technology has a leading position in research and education. The Department currently has about 300 employees, including 120 teachers and 110 PhD students. More than 4000 students study one or more courses at the department each year. You can find more information about us at the web page of the department of Information Technology
The Department is situated in the newly built Ångström House 10, which contains a visualization studio, a social robot lab, a maker space and 3D printing workshop. Researchers work in all areas of IT, from designing processers, through HCI, cybersecurity, control, to cancer research tools and methods for numerical analysis and machine learning.

Uppsala University’s has a long tradition of successful research – among its alumni are 16 Nobel Prize laureates, including, most recently, Svante Pääbo. The University is unique when it comes to combining IT with wider research, from life sciences to the humanities, and this collaboration is currently facilitated by AI4Research and the Centre for Interdisciplinary Mathematics.

Read more about our benefits and what it is like to work at Uppsala University

At the Division of Systems and Control, we develop both theory and concrete tools for learning, reasoning, and acting based on data. An overarching goal is for both humans and machines to better understand the complexity of the real world. Probabilistic models form a central part of our research, allowing us to systematically represent and cope with the uncertainty inherent in most data. Data, learning and decision/control algorithms are also important components of our research. We have a wide network of strong international collaborators all around the world, for example at the University of Cambridge, University of Oxford, University of Sydney, University of Newcastle and Aalto University. There are also ample opportunities for collaborations with other leading machine learning groups in Sweden and Europe, through our affiliations with WASP and the ELLIS society, respectively. 

Duties/Project description
Research on fundamental models and methods in control and machine learning, in particular at the intersection of control and machine learning. As systems become increasingly complex and the amount of available data grows, reliable and efficient data-driven methods for control become more crucial. The aim of this project is to develop new models, methods and theory/analysis for data-driven approaches to learning a controller. As such, the project should be grounded in control and/or machine learning. The specific methods and theory will be decided on together with the successful applicant.

Technical keywords for the position include: Data-driven control, Foundations of learning of dynamics models, System identification, Data-driven optimization for dynamical systems, Reinforcement learning for physical systems, Safe reinforcement learning, Statistical learning for dynamical and control systems. 

The position can include teaching up to 20% depending on availability and interest. 

PhD degree within control, machine learning, signal processing, computer vision, computational statistics or another nearby and relevant field or a foreign degree equivalent to a PhD degree within control, machine learning, signal processing, computer vision, computational statistics or another nearby and relevant field. The degree needs to be obtained by the time of the decision of employment. Those who have obtained a PhD degree three years prior to the application deadline are primarily considered for the employment. The starting point of the three-year frame period is the application deadline. Due to special circumstances, the degree may have been obtained earlier. The three-year period can be extended due to circumstances such as sick leave, parental leave, duties in labour unions, etc.

The applicant must have a strong background in method development.

Publications at leading conferences in machine learning and/or leading conferences and journals in control is a strong plus.

You are expected to be able to teach in Swedish or English. Excellent knowledge of oral and written English is a requirement.

Additional qualifications
As a person, you are creative, thorough and have a structured approach. When selecting among the applicants we will assess their ability to independently drive their work forward, to collaborate with others, to have a professional approach and to analyze and work with complex problems. Great emphasis will be placed on personal characteristics and personal suitability.

Application: The application must contain:

  1. A curriculum vitae (CV),
  2. A copy of relevant grade documents (translated into Swedish or English),
  3. A list of publications
  4. Up to five selected publications in electronic format
  5. A research statement describing your past and current research (max 1 page) and a proposal for future activities (max 1 page).
  6. Contact information for two references.
  7. A cover letter briefly describing your motivation for applying for this position and the earliest possible employment date (max 1 page).

About the employment
The employment is a temporary position of 2 years according to central collective agreement. Scope of employment 100%. Starting date, as agreed. Placement: Uppsala.

For further information about the position, please please see: http://www.it.uu.se/ (the department) or contact: Prof. Thomas Schön (thomas.schon@it.uu.se) or Assistant Professor Per Mattsson (per.mattsson@it.uu.se).

Please submit your application by 14th of April 2023, UFV-PA 2023/852.

Are you considering moving to Sweden to work at Uppsala University? Find out more about what it´s like to work and live in Sweden.  

Type of employment Temporary position
Contract type Full time
First day of employment As soon as possible
Salary Fixed salary
Number of positions 1
Full-time equivalent 100%
City Uppsala
County Uppsala län
Country Sweden
Reference number UFV-PA 2023/852
Union representative
  • Seko Universitetsklubben, seko@uadm.uu.se
  • ST/TCO, tco@fackorg.uu.se
  • Saco-rådet, saco@uadm.uu.se
Published 03.Mar.2023
Last application date 14.Apr.2023 11:59 PM CEST

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