We have an exciting new PhD position in visual analytics of multi-layer networks

The Visual Data Analysis research group at KU Leuven (University of Leuven) is part of the department of Biosystems at the Faculty of Bioscience Engineering. The group focusses on complex data exploration in the domain of biological and agricultural sciences, through the use of visual analytics and topological data analysis. The group is currently looking for a dynamic and highly motivated PhD student.

Project

Networks and graphs - both static and dynamic - play an important role in data science. Not only can they represent primary relational data (e.g. gene interactions) but many algorithms generate networks either as intermediate or final output (e.g. DBSCAN clustering and topological data analysis). In particular, these data structures are critical when investigating (biological and other) systems as a whole.

We can quantitatively compare networks at different resolutions, and distinguish between changes in topology and changes in characteristics of the nodes and links themselves. Although many measures exist to do so (including degree, closeness, betweenness, etc), they mainly focus on the amount of difference but fall short in giving real insight in the quality of that difference. We want to focus on this qualitative understanding of networks rather than only a quantitative one.

We want to develop a human-in-the-loop visual analytics toolkit to support the user in exploring differences between two or more networks in depth. Visual Analytics (VA) is often described as the science of analytical reasoning facilitated by the visual interface and combines interactive data visualisation and novel visual design on one hand with machine learning on the other.

The methodology will involve - among other things - custom visual design, definition and implementation of interestingness features, as well as definition of novel distance metrics for topological data analysis. This will be applied to different types of multi-layer networks (e.g. with/without ordering in 2 or more dimensions).

Keywords: graph, network, topological data analysis, visual analytics, data visualisation, multilayer networks

Example papers on the topic of multi-layer networks and topological data analysis:
Profile
The Ideal Candidate
Interested Candidates Should Submit The Following
Offer

How to apply
For more information on this opportunity, please contact Prof Jan Aerts, tel.: +32 16 32 21 40, mail: jan.aerts@kuleuven.be
You can apply via the KU Leuven jobsite at https://www.kuleuven.be/personeel/jobsite/jobs/60288125
Deadline for submitting: 11/1/2024


---
Prof Jan Aerts
Visual Data Analysis Lab
Department of Biosystems
KU Leuven, Belgium
jan.aerts@kuleuven.be
https://www.biw.kuleuven.be/biosyst ; http://vda-lab.io