Postdoctoral Fellows in Machine Learning
Uppsala University Department of Information Technology

Up to three Postdoctoral fellows in Machine Learning – fundamental models and methods

Published: 2021-04-29

Uppsala University is a comprehensive research-intensive university with a strong international standing. Our ultimate goal is to conduct education and research of the highest quality and relevance to make a long-term difference in society. Our most important assets are all the individuals whose curiosity and dedication make Uppsala University one of Sweden’s most exciting workplaces. Uppsala University has over 45,000 students, more than 7,000 employees and a turnover of around SEK 7 billion.

The Department of Information Technology has a leading position in research and education. The Department currently has about 280 employees, including 120 teachers and 110 PhD students. More than 4000 students study one or more courses at the department each year. More info: lang=en.

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 and learning algorithms are also important components of our research. It remains a major challenge to develop efficient and accurate learning algorithms capable of handling high-dimensional models, data rich applications, complex model structures, and diverse data sources that arise in many of the data analysis problems that we are currently facing.

The Division of Systems and Control has a wide network of strong international collaborators all around the world, for example at the University of Cambridge, University of Oxford, University of British Columbia, 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.

One of the positions is funded by Wallenberg AI, Autonomous Systems and Software Program (WASP), Sweden’s largest individual research program ever, and a major national initiative for strategically motivated basic research, education and faculty recruitment. The program addresses research on artificial intelligence and autonomous systems acting in collaboration with humans, adapting to their environment through sensors, information, and knowledge, and forming intelligent systems-of-systems.

The vision of WASP is excellent research and competence in artificial intelligence, autonomous systems, and software for the benefit of Swedish industry. Read more:

Duties/Project description: Research on fundamental methods in machine learning. Links to related fields such as optimization, control and computer vision are also possible. These postdoctoral positions will intensify our work (on both method development and applications) in machine learning and may, if the candidate wishes, be paired with real-world applications in e.g. robotics, natural sciences, or climate change action. The position might also include teaching in machine learning.

Requirements: To qualify for an employment as a postdoctoral fellow you must have a PhD degree or a foreign degree equivalent to a PhD degree in a relevant field. The PhD degree must have been obtained no more than three years prior to the application deadline. The three-year period can be extended due to circumstances such as sick leave, parental leave, duties in labor unions, etc.

The applicant must have a strong background in method development and the use of machine learning. Publications at leading conferences in machine learning is a strong plus.

Other qualifications: Experience of interdisciplinary research is good. 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.

The employment is for two years and can include teaching up to 20% depending on availability and interest. You are expected to be able to teach in Swedish or English. Excellent knowledge of oral and written English is a requirement.

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)

Salary: Individual salary.
Starting date: As soon as possible.

Type of employment: Temporary position according to central collective agreement.

Scope of employment: 100 %

For further information about the position please see: (the department) or contact: Prof. Thomas Schön ( or Assistant Professor Jens Sjölund (

Please submit your application by 4 June 2021, UFV-PA 2021/1610.

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. 

Please do not send offers of recruitment or advertising services.

Submit your application through Uppsala University's recruitment system.

Placement: Department of Information Technology

Type of employment: Full time , Temporary position longer than 6 months

Pay: Fixed salary

Number of positions: 3

Working hours: 100 %

Town: Uppsala

County: Uppsala län

Country: Sweden

Union representative: Seko Universitetsklubben

Number of reference: UFV-PA 2021/1610

Last application date: 2021-06-04

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