Flanders.bio
Research Scientist - Visual Analytics for Network Comparison (ref...
Flanders.bio - Belgium, West Virginia, United States,Work at Flanders.bio
Overview
- Apply
Overview
Research Scientist - Visual Analytics for Network Comparison (ref. BAP-2023-626)
Research Scientist - Visual Analytics for Network Comparison (ref. BAP-2023-626)
22/09/23Location
Vacancy
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.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).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. 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 - requirement elicitation, 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 networksProfileThe candidate should have a Master's degree in Computer Science, Bioscience Engineering or similar. In addition, they should have a solid understanding of network analysis and a strong foundation in general data visualisation principles and techniques.Interested candidates should submit their curriculum vitae, contact information of 2 or 3 referees, and a motivation letter. This motivation letter should specify why the candidate applies to this position, and clearly illustrate possible past experience in the area.OfferA full-time PhD position for one year; after a positive evaluation, the contract can be extended to three additional years (four years in total)A working climate where trust, (international) collaboration, and commitment are essentialAn excellent young, stimulating and supportive international research environmentHigh level scientific training at a top-ranked university; training in academic, thematic and soft skills.For more information please contact Prof. dr. ir. Jan Aerts, tel.: +32 16 32 21 40, mail: jan.aerts@kuleuven.be.KU Leuven seeks to foster an environment where all talents can flourish, regardless of gender, age, cultural background, nationality or impairments. If you have any questions relating to accessibility or support, please contact us at diversiteit.HR@kuleuven.be.Job application
First nameLast nameEmailResumeMessageBy filling out this form, I acknowledge that my data are collected and processed only by flanders.bio and the company responsible for this vacancy.
#J-18808-Ljbffr
Research Scientist - Visual Analytics for Network Comparison (ref. BAP-2023-626)
22/09/23Location
Vacancy
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.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).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. 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 - requirement elicitation, 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 networksProfileThe candidate should have a Master's degree in Computer Science, Bioscience Engineering or similar. In addition, they should have a solid understanding of network analysis and a strong foundation in general data visualisation principles and techniques.Interested candidates should submit their curriculum vitae, contact information of 2 or 3 referees, and a motivation letter. This motivation letter should specify why the candidate applies to this position, and clearly illustrate possible past experience in the area.OfferA full-time PhD position for one year; after a positive evaluation, the contract can be extended to three additional years (four years in total)A working climate where trust, (international) collaboration, and commitment are essentialAn excellent young, stimulating and supportive international research environmentHigh level scientific training at a top-ranked university; training in academic, thematic and soft skills.For more information please contact Prof. dr. ir. Jan Aerts, tel.: +32 16 32 21 40, mail: jan.aerts@kuleuven.be.KU Leuven seeks to foster an environment where all talents can flourish, regardless of gender, age, cultural background, nationality or impairments. If you have any questions relating to accessibility or support, please contact us at diversiteit.HR@kuleuven.be.Job application
First nameLast nameEmailResumeMessageBy filling out this form, I acknowledge that my data are collected and processed only by flanders.bio and the company responsible for this vacancy.
#J-18808-Ljbffr