Postdoctoral position in Machine Learning for Control
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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.
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.
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:
- A curriculum vitae (CV),
- A copy of relevant grade documents (translated into Swedish or English),
- A list of publications
- Up to five selected publications in electronic format
- A research statement describing your past and current research (max 1 page) and a proposal for future activities (max 1 page).
- Contact information for two references.
- 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 (email@example.com) or Assistant Professor Per Mattsson (firstname.lastname@example.org).
Please submit your application by 14th of April 2023, UFV-PA 2023/852.
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Submit your application through Uppsala University's recruitment system.
Placement: Department of Information Technology
Type of employment: Full time , Temporary position
Pay: Fixed salary
Number of positions: 1
Working hours: 100%
County: Uppsala län
Number of reference: UFV-PA 2023/852
Last application date: 2023-04-14
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