Postdoctoral Position - Decision Making with Limited Data using Artificial Intelligence

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Postdoctoral Position - Decision Making with Limited Data using Artificial Intelligence

Uppsala University
Country of Position: 
Contact Name: 
Ayca Ozcelikkale
Subject Area: 
Machine Learning for Signal Processing
Start Date: 
25 March 2020
Expiration Date: 
01 April 2020
Position Description: 

Postdoctoral Position - Decision Making with Limited Data using Artificial Intelligence - An Active Inference Approach

Signals and Systems Division, Department of Electrical Engineering,  Uppsala University has a vacancy for a postdoctoral position. The position is a part of the strategic research area effort eSSENCE´s PostDoc-program towards new e-science methods and tools for artificial intelligence in research.

Project description: Success of machine learning (ML) and artificial intelligence (AI) methods typically rely on the availability of large amounts of data. This dependence on high amounts of data/interactions is an important handicap for applying the current AI approaches in data-limited scenarios, such as Internet-of-Things scenarios. This project will address this handicap of limited data using the active inference (ActInf) framework. Similar to the reinforcement learning, the ActInf framework generates actions/policies so that a specific desired outcome is obtained by interacting with the surroundings. ActInf is closely connected to probabilistic dynamical models, belief propagation, and model based reinforcement learning. ActInf can also be used to recover standard cost-based control solutions for the linear quadratic setup, a well-known scenario which is of central importance in the control community.

Duties: To conduct original research in the area of decision making under limited data  using the ActInf framework, in particular i) develop novel, general-purpose, active inference based adaptive data collection, decision making and control strategies to optimize the overall inference and control performance under limited data,  ii) reveal the trade-offs between data collection, decision making and control performance and provide guidelines for cost-efficient autonomous operation for various application scenarios.

The duties include theoretical analysis, algorithm design and implementation via software-based simulations, and reporting of the results in the form of technical papers. Participation in the undergraduate and/or graduate education and supervision of PhD students is also required.

Requirements: PhD degree or a foreign degree equivalent to a PhD degree in Electrical Engineering or Computer Science with a background in Automatic Control, Signal Processing, Machine Learning or Communications. 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 labour unions, etc.

A proven publication record in top-ranked journals or conferences is required. Emphasis will be placed on computer programming abilities together with a strong mathematical background where previous research in active inference or closely related areas such as probabilistic dynamical models, information theory, optimization theory or reinforcement learning will be beneficial.

Starting date: 2020-06-01 or as otherwise agreed.

Further Information: The complete announcement text can be found here:

For further information do not hesitate to contact Ayca Özcelikkale, or  Anders Ahlén,

Application Instructions: Please submit your application by April 1, 2020 through Uppsala University´s recruitment system:

Note that applications by email cannot be considered.




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