Postdoctoral position – Decision Making with Limited Data using Artificial Intelligence - Hiring in process/Finished, not possible to apply

The position will be located at the Department of Electrical Engineering at the Signals and Systems Division, The Angström Laboratory. 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.

It is for two years starting 2020-11-01 or as soon as possible thereafter.

Background: 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. We will consider a framework that generates actions/policies so that a specific desired outcome is obtained by interacting with the surroundings. Our approach will be closely connected to probabilistic dynamical models and model based reinforcement learning.

Duties: To conduct original research in the area of decision making under limited data, in particular i) develop novel, general-purpose 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.

Qualifications required: A PhD 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.

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 related areas such as probabilistic dynamical models, information theory, optimisation theory, reinforcement learning or active inference will be beneficial.

Application: The application must include:

• CV including full publication list
• Contact information for at least two references
• Personal letter which includes a brief account of your previous research field(s) and main research results as well as your future goals and future research focus (1-3 pages)

You do not need to upload publications or fill in the publication list within the system as long as this information is available on your CV.

Salary: Individual salary.

Starting date: 2020-11-01 or as otherwise agreed.

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

Scope of employment: 100 %

For further information about the position please contact: Assistant Professor Ayca Özcelikkale, ayca.ozcelikkale@angstrom.uu.se or Professor Anders Ahlén, anders.ahlen@signal.uu.se. Information about the division Signals and Systems, www.signal.uu.se.

Please submit your application by 8 October 2020, UFV-PA 2020/3261.

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