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Sender: "ACM SIGCHI General Interest Announcements (Mailing List)" <[log in to unmask]>
Date: Thu, 5 Aug 2021 07:26:39 +0000
Reply-To: Andreas Kerren <[log in to unmask]>
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From: Andreas Kerren <[log in to unmask]>
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*** Apologies for cross-posting ***

We are seeking for an engaged and bright PhD student to work with us in the areas of Information Visualization and Visual Analytics. The main focus of the advertised position (ref. LiU-2021-02831) is the visual analysis of large and complex, multivariate networks and/or text data. 

Research in this doctoral project will involve foundational visualization principles, techniques and visual analytics tools for analyzing heterogeneous network/text data coming from various data sources. The work will even include the development and provisioning of a suitable backend infrastructure to serve the web-based, interactive visual display with the needed original and derived data streams, and/or user data collected during the analytical process. Main supervisor will be Prof Andreas Kerren ([log in to unmask]). Please visit the official vacancy website of Linköping University for a more detailed description of the topic, formal requirements, and on how to apply for this position:

The application deadline is August 20, 2021.

Note that a PhD position in Sweden is a salaried employment with the right to social benefits. As a doctoral student, you devote most of your time to doctoral studies and the research projects of which you are part. Your work may also include teaching or other departmental duties, up to a maximum of 20% of full-time. The PhD thesis must be completed and defended within the official appointment up to a maximum of five years (i.e., 4 years doctoral studies and 1 year departmental tasks, full-time equivalent).

The advertised position will be placed in the iVis research group ( led by Prof Andreas Kerren, Linköping University, Norrköping Campus, which is part of the division for Media and Information Technology. The research group mainly focuses on the explorative analysis and visualization of typically large and complex information spaces, for example in the life sciences, humanities, or environmental sciences. Our research vision is to attack the big data challenge through the combination of human-centered data analysis and interactive visualization for decision making. These research topics are highly relevant for academia and economy as both science and industry make increasing use of data-intensive technologies.

Please share this message with any great candidates.

Best regards,
Andreas Kerren
iVis Group @ Linköping University

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