2022-12-04: Job: PostDoc Position in Information Visualization / Visual Analytics at Linnaeus University, Sweden. (Deadline: January 9, 2023)

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PostDoc Fellowship in Information Visualization and Visual Analytics

placed at Linnaeus University, Department of Computer Science and Media Technology, Faculty of Technology – Växjö Campus, Sweden

Your workplace

The advertised position will be placed in the ISOVIS group, led by Professor Andreas Kerren. The research group mainly focuses on the explorative analysis and visualization of typically large and complex information spaces, for example in biochemistry, humanities, or software engineering. Our vision is to attack the big data challenge by a 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.

Your work assignments

The postdoc fellow will conduct research within the fields of information visualization and visual analytics in close collaboration with ISOVIS members, other research groups of the department, and domain experts within the Linnaeus University Centre for Data Intensive Sciences and Applications (DISA). The work duties include the whole research cycle, i.e., from literature reviews and the identification of research challenges, throughout the implementation of visualization tools and performing user studies, to the reporting of the results in publications.

In this context, the postdoc fellow is expected to regularly present intermediate/final research results at international conferences/workshops and publish them in highly-ranked conference proceedings and journals in the areas of information visualization, visual analytics, but possibly also in the areas of the domain experts.

Within the DISA environment, large and complex data sets from various domain areas need to be efficiently visualized to transform data into useful information and new knowledge by the development of visualization principles, techniques and visual analytics tools, including provisioning suitable backend infrastructures to serve web-based, interactive visualizations.

To the extent of maximal 20% of the working time, the postdoc fellow will be involved in teaching activities at different levels (incl. supervision of Bachelor’s and Master’s thesis projects). The teaching tasks relate to subjects of the ISOVIS research group, as well as to more general courses in computer science and software development.

Your qualifications

Eligible to be employed are those who have completed a doctoral degree in Computer Science or an equivalent degree. The doctorate shall have been obtained no longer than three years before the expiration date of the application. Eligibility for this position also requires that the doctoral thesis has a focus on information visualization, visual analytics, or closely related fields. Excellent written and oral communication skills in English are required.

Excellent knowledge in the focused research areas of information visualization and visual analytics is a strong advantage. Good programming skills (Java, JavaScript, HTML5, WebGL/OpenGL) and a solid training in mathematics, data mining, or machine learning are highly preferred. Experience of teaching at undergraduate and/or advanced levels in the field is desirable. Documented expertise and working experience within at least one of the following research and educational areas is a great advantage:

  • Visual analytics of Big Data
  • Multidimensional visualization techniques in combination with machine learning and/or data mining techniques
  • Visual text/network/software analytics
  • Explainable AI/ML using visualization
  • Experiences in specific application domains and their visualization needs, such as in digital humanities, social sciences, engineering sciences, life sciences, etc.

Teamwork experiences should also be documented in the application. Since the subject is male-dominated, we encourage female applicants. Proven track record of publication will be preferable. Applicants will be selected through a qualitative overall assessment of the competences and skills, assessed most suitable to conduct research and to contribute to a successful development of the research environment.

How to apply

Interested candidates find detailed application information including terms of employment, needed documents, and contact details on the following web page


Online applications (reference number: 2022/1019-2.2.1) will be received until January 9, 2023.