Postdoc in Information Visualization and Visual Analytics

Linköping University

Application deadline

February 28, 2022

Postdoc in Information Visualization and Visual Analytics

Skilled and committed employees are a crucial factor in the success of Linköping University. And we need more of them. Our core expertise comes from teachers and researchers, but a successful university requires experienced and motivated employees in many fields. Everyone is important. We need to recruit many new employees thanks to, among all, an expansion in our research activity. We need you here. We look forward to receiving your application!

At the Department of Science and Technology, at the university’s Norrköping campus, we provide education and conduct research in physics and electronics, communications/logistics and media- and information technology. The department is recognised for its work in fields including logistics, visualisation and organic electronics. We combine academic excellence with fruitful collaboration with the Community.

We are now looking to appoint a postdoc in Information Visualization and Visual Analytics

Research area
The advertised position will be affiliated to the Information Visualization research unit (iVis) led by Professor Andreas Kerren (see The research group mainly focuses on the explorative analysis and visualization of typically large and complex information spaces, for example in environmental research, transportation systems, social sciences, or artificial intelligence. Our vision is to attack the big data challenge by a combination of human-centered data analysis and interactive visualization for deriving meaning from the data and final decision making. Our research is highly relevant for academia and industry as both make increasing use of data-intensive technologies.

This position is part of a joint collaboration between the two largest research programs in Sweden, the Wallenberg AI, Autonomous Systems and Software Program (WASP) and the SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS), with the ultimate goal of solving ground-breaking research questions across disciplines.

Wallenberg AI, Autonomous Systems and Software Program (WASP) is Sweden’s largest individual research program ever, a major national initiative for strategically motivated basic research, education and faculty recruitment. The program addresses research on artificial intelligence and autonomous systems acting in collaboration with humans, adapting to their environment through sensors, information and knowledge, and forming intelligent systems-of- systems. The vision of WASP is excellent research and competence in artificial intelligence, autonomous systems and software for the benefit of Swedish industry. Read more:

The above-mentioned collaboration between WASP and DDLS will be performed in the context of an interdisciplinary research project entitled “Visual Analytics for Enhancing Quality and Trust in Genome-wide Expression Clustering and Annotation”, where the Systems Biology group at the Royal Institute of Technology (KTH) and the Information Visualization group at Linköping University (LiU) work closely together.

There is a need for a functional genome-wide annotation of the protein-coding genes to get a deeper understanding of mammalian biology. The new data-driven strategy to be developed in the project is based on interpretable unsupervised learning (e.g., dimensionality reduction and clustering) of whole-body co-expression patterns, supported by state-of-the-art visual analytics. Interactive guiding of the clustering process will be used to explore the gene expression landscape in humans and other mammalian species, and to create a whole-body map of all protein-coding genes in all major cell types, tissues and organs. This will allow for the improvement of the quality of the classification of all protein-coding genes according to their whole-body co-expression patterns, resulting in every gene being annotated to a unique expression cluster together with other genes with a similar body-wide pattern.

The focus of this advertised Postdoc position at LiU will be on research and development of an interactive and interpretable (human-in-the-loop) clustering strategy to reach these goals. The successful candidate will develop visual analytics approaches that provide fine-grained quality analysis of the clustering processes and better interpretation/annotation of clusters.

Duties consist mainly of the following:
· Research within the fields of information visualization and visual analytics (in context of the project aims).
· Regularly present intermediate/final research results at international conferences and workshops, and publish them in top-tier conference proceedings and journals.
· Close collaboration with the other project members in our interdisciplinary research project (especially with the second Postdoc to be hired in the partner group at KTH) as well as domain experts in the life sciences.

As postdoc, you will principally carry out research. A certain amount of teaching may be part of your duties, up to a maximum of 20% of working hours.

To be qualified to take employment as postdoc, you must have been awarded a doctoral degree or have a foreign degree that is deemed to be equivalent to a doctoral degree.  This degree must have been awarded at the latest by the point at which LiU makes its decision to employ you.

It is considered advantageous if your doctoral degree is no older than three years at application deadline for this job. If there are special reasons for having an older doctoral degree – such as taking statutory leave – then these may be taken into consideration.

Eligibility for this position also requires a PhD degree in Computer/Data Science and that the doctoral thesis has a focus on information visualization, visual analytics, or closely related fields.

Excellent knowledge in the focused research area of information visualization and visual analytics is a strong advantage. Research experiences in the visual analysis of biological data sets are a great asset as well. Good programming skills (Java, JavaScript / HTML5, WebGL/OpenGL) and a solid training in mathematics, data mining, or machine learning are highly preferred. Knowledge and experience in one or more of the following areas would be advantageous: information visualization, visual analytics, human-computer interaction, data mining, unsupervised learning (dimensionality reduction and clustering), supervised machine learning.

Excellent written and oral communication skills in English are required. Teamwork experiences should also be documented in the application.

Great emphasis will be placed on personal qualities and suitability.

Last updated: 2022-01-24

Content Responsible: David Gotthold(