Are you interested in working with state-of-the-art machine learning methods with the support of competent and friendly colleagues in an international environment? Are you looking for an employer that invests in sustainable employeeship and offers safe, favorable working conditions? We welcome you to apply for a postdoctoral position at Uppsala University.
Uppsala University 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.
The Department of Information Technology holds a leading position in both research and education at all levels. We are currently Uppsala University's third largest department, have around 350 employees, including 120 teachers and 120 PhD students. Approximately 5,000 undergraduate students take one or more courses at the department each year.
At the Division of Systems and Control, we develop both theory and concrete tools to design systems that learn, reason, and act in the real world based on a seamless combination of data, mathematical models, and algorithms. Our research integrates expertise from machine learning, optimization, control theory, and applied mathematics, spanning diverse application domains such as medicine, energy systems, biomedical systems, neuroscience, and safety and security.
We have a wide network of long-standing international collaborators all around the world, for example at the University of Cambridge, University of Oxford, Imperial College London, University of Sydney, University of Newcastle and Aalto University.
Duties: Research on fundamental models and methods in machine learning and their applications in medicine. We will continue our work on extracting knowledge from large-scale ECG datasets and possibly also related data. The aim is to be able to investigate the use of these models for decision support and the position may also include work on decision algorithms. The postdoctoral researcher will collaborate with our colleagues at the Faculty of Medicine here in Uppsala and likely also with our partners in Brazil.
Technical keywords for the position include probabilistic models, deep learning, decision algorithms, Bayesian inference and precision medicine. The position may include teaching up to 20% depending on availability and interest.
Requirements: PhD degree in machine learning, control, signal processing, computational statistics or another nearby relevant area or a foreign degree equivalent to a PhD degree in machine learning, control, signal processing or computational statistics. The degree needs to be obtained by the time of the decision of employment. Priority will be given to applicants who have completed their degree no more than three years before the deadline for applications. 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.
We are looking for candidates with:
Publications at leading conferences in machine learning is a big plus. You are expected to be able to teach in Swedish or English.
Additional qualifications: Experience in interdisciplinary research is a plus. As a person, you are creative, meticulous and have a structured approach. When selecting 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 importance will be placed on personal qualities and personal suitability.
The application must contain:
About the employment: The employment is a temporary position of 2 years according to central collective agreement. Full time position. Starting date October 1, 2026 or as agreed. Placement: Uppsala.
For further information about the position, please contact: Professor Thomas Schön, 018 – 471 25 94, thomas.schon@uu.se
Please submit your application by August 28, 2026, UFV-PA 2026/2006.
Tagged as: Life Sciences
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